空氣汙染引起 EGFR基因突變肺癌

穹頂之下空氣汙染造成基因突變

Thomas Lin M.D.林宗諭 M.D.

穹頂之下

1. 肺癌：寂靜殺⼿手

2. 暴露致癌物引起基因突變，基因突變導致癌症3. ⾎血液 cfDNA 帶有基因突變4. EGFR基因突變警⽰示肺癌罹患⾵風險5. EGFR基因突變輔助肺癌篩檢

In contrast to the stable or declining trends for mostcancers, incidence rates in the SEER 13 registriesincreased from 2007 through 2011 among both menand women for cancers of the small intestine, anus,liver, pancreas, soft tissue (including the heart), andthyroid; melanoma of the skin; myeloma; and leuke-mia.7,17 In addition, incidence rates increased in men

for breast cancer, non-Hodgkin lymphoma, and humanpapillomavirus-positive oropharyngeal cancers and inwomen for esophageal adenocarcinoma and uterine can-cer. The largest annual increases were for cancers of thethyroid (5.3% and 4.5% in men and women, respec-tively) and liver (3.6% and 2.9% in men and women,respectively) (Table 5).

FIGURE 5. Trends in Death Rates Overall and for Selected Sites by Sex, United States, 1930 to 2011.Rates are age adjusted to the 2000 US standard population. Due to changes in International Classification of Diseases (ICD) coding, numerator informationhas changed over time. Rates for cancers of the lung and bronchus, colorectum, liver, uterus, and ovary are affected by these changes.*Mortality rates for pancreatic and liver cancers are increasing.†Uterus includes uterine cervix and uterine corpus.

Cancer Statistics, 2015

18 CA: A Cancer Journal for Clinicians

In contrast to the stable or declining trends for mostcancers, incidence rates in the SEER 13 registriesincreased from 2007 through 2011 among both menand women for cancers of the small intestine, anus,liver, pancreas, soft tissue (including the heart), andthyroid; melanoma of the skin; myeloma; and leuke-mia.7,17 In addition, incidence rates increased in men

for breast cancer, non-Hodgkin lymphoma, and humanpapillomavirus-positive oropharyngeal cancers and inwomen for esophageal adenocarcinoma and uterine can-cer. The largest annual increases were for cancers of thethyroid (5.3% and 4.5% in men and women, respec-tively) and liver (3.6% and 2.9% in men and women,respectively) (Table 5).

FIGURE 5. Trends in Death Rates Overall and for Selected Sites by Sex, United States, 1930 to 2011.Rates are age adjusted to the 2000 US standard population. Due to changes in International Classification of Diseases (ICD) coding, numerator informationhas changed over time. Rates for cancers of the lung and bronchus, colorectum, liver, uterus, and ovary are affected by these changes.*Mortality rates for pancreatic and liver cancers are increasing.†Uterus includes uterine cervix and uterine corpus.

Cancer Statistics, 2015

18 CA: A Cancer Journal for Clinicians

台灣 10 大癌症，按發生率及死亡率排序（以年齡標準化率 2b排序） 10 大癌症（不含原位癌 5）發生率（每 10 萬人口），民國 101 年順位 ICD-O-3 原發部位

個案數（人）

粗發生率年齡標準化發生率 2a

年齡標準化發生率 2b

1 C50 女性乳房 10,525 90.40 6a 61.21 65.93 2 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 14,965 64.18 39.80 45.10 3 C22 肝及肝內膽管 11,422 48.99 31.39 35.02 4 C33-C34 肺、支氣管及氣管 11,692 50.15 30.56 34.99 5 C61 攝護腺 4,735 40.56 6b 25.02 29.70 6 C00-C143 口腔、口咽及下咽 7,047 30.22 20.67 22.27 口腔 4,716 20.23 13.89 14.99 口咽 1,322 5.67 3.86 4.15 下咽 1,009 4.33 2.92 3.13

7 C54 子宮體 1,936 16.63 6a 11.08 11.96 8 C16 胃 3,796 16.28 9.57 11.11 9 C73 甲狀腺 2,895 12.42 6a 9.12 9.90 10 C444 皮膚 3,274 14.04 8.16 9.65

C00-C80 全癌症 96,694 414.71 269.06 300.01

10 大癌症（含原位癌 5）發生率（每 10 萬人口），民國 101 年

順位 ICD-O-3 原發部位個案數（人）



1 C50 女性乳房 12,501 107.37 6a 72.91 78.32 C50 女性乳房原位癌 1,976 16.97 6a 11.70 12.39 C50 女性乳房侵襲癌 10,525 90.40 6a 61.21 65.93

2 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 16,448 70.54 44.02 49.68 3 C33-C34 肺、支氣管及氣管 11,713 50.24 30.63 35.06 4 C22 肝及肝內膽管 11,427 49.01 31.41 35.03 5 C53 子宮頸 4,826 41.45 6a 28.94 32.07 C53 子宮頸原位癌 3,259 27.99 6a 20.30 22.47 C53 子宮頸侵襲癌 1,567 13.46 6a 8.64 9.60

6 C61 攝護腺 4,740 40.61 6b 25.05 29.73 7 C00-C143 口腔、口咽及下咽 7,111 30.50 20.85 22.47 口腔 4,753 20.39 14.00 15.10 口咽 1,333 5.72 3.90 4.18 下咽 1,025 4.40 2.96 3.18

8 C54 子宮體 1,939 16.65 11.10 11.98 9 C16 胃 3,843 16.48 6a 9.68 11.25 10 C444 皮膚 3,569 15.31 8.87 10.50 C00-C80 全癌症 105,082 450.69 293.90 327.30

10 大癌症死亡率（每 10 萬人口），民國 101 年

順位 ICD-10 原發部位個案數（人）

粗死亡率年齡標準化死亡率 2a

年齡標準化死亡率 2b

1 C33-C34 肺、支氣管及氣管 8,587 36.83 21.31 25.02 2 C22 肝及肝內膽管 8,116 34.81 21.28 24.37 3 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 5,131 22.01 12.32 14.69 4 C50 女性乳房 1,912 16.42 6a 10.53 11.47 5 C00-C143 口腔、口咽及下咽 2,566 11.01 7.36 8.00 6 C16 胃 2,386 10.23 5.70 6.78 7 C61 攝護腺 1,187 10.17 6b 5.17 6.63 8 C15 食道 1,581 6.78 4.44 4.82 9 C25 胰 1,629 6.99 4.13 4.78 10 C53 子宮頸 669 5.75 6a 3.37 3.85 C00-C97 全癌症 43,665 187.28 112.36 129.48

註： 1. 自 96 年癌症登記報告起，淋巴瘤從各部位獨立出來計算發生率，並納入排名。淋巴瘤：ICD-O-3 M-CODE 請見 p.495 附錄五。 2. 年齡標準化率 2a係使用 1976 年世界標準人口為標準人口。年齡標準化率 2b係使用 2000 年世界標準人口為標準人口。 3. 口腔、口咽及下咽原發部位代碼包括 ICD-O-3 & ICD-10：C00-C06、C09-C10、C12-14。細分類代碼請見 p.18。 4. 皮膚原發部位包括基底細胞癌個案。 5. 原位癌：組織形態之分類碼第 5 碼（性態譯碼）為 2。 6. (a)每 10 萬女性人口粗發生率及粗死亡率；(b)每 10 萬男性人口粗發生率及粗死亡率

- 3 -

中華⺠民國 101 年癌症登記報告

台灣 10 大癌症，按發生率及死亡率排序（以年齡標準化率 2b排序） 10 大癌症（不含原位癌 5）發生率（每 10 萬人口），民國 101 年順位 ICD-O-3 原發部位

個案數（人）



1 C50 女性乳房 10,525 90.40 6a 61.21 65.93 2 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 14,965 64.18 39.80 45.10 3 C22 肝及肝內膽管 11,422 48.99 31.39 35.02 4 C33-C34 肺、支氣管及氣管 11,692 50.15 30.56 34.99 5 C61 攝護腺 4,735 40.56 6b 25.02 29.70 6 C00-C143 口腔、口咽及下咽 7,047 30.22 20.67 22.27 口腔 4,716 20.23 13.89 14.99 口咽 1,322 5.67 3.86 4.15 下咽 1,009 4.33 2.92 3.13

7 C54 子宮體 1,936 16.63 6a 11.08 11.96 8 C16 胃 3,796 16.28 9.57 11.11 9 C73 甲狀腺 2,895 12.42 6a 9.12 9.90 10 C444 皮膚 3,274 14.04 8.16 9.65

C00-C80 全癌症 96,694 414.71 269.06 300.01

10 大癌症（含原位癌 5）發生率（每 10 萬人口），民國 101 年

順位 ICD-O-3 原發部位個案數（人）



1 C50 女性乳房 12,501 107.37 6a 72.91 78.32 C50 女性乳房原位癌 1,976 16.97 6a 11.70 12.39 C50 女性乳房侵襲癌 10,525 90.40 6a 61.21 65.93

2 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 16,448 70.54 44.02 49.68 3 C33-C34 肺、支氣管及氣管 11,713 50.24 30.63 35.06 4 C22 肝及肝內膽管 11,427 49.01 31.41 35.03 5 C53 子宮頸 4,826 41.45 6a 28.94 32.07 C53 子宮頸原位癌 3,259 27.99 6a 20.30 22.47 C53 子宮頸侵襲癌 1,567 13.46 6a 8.64 9.60

6 C61 攝護腺 4,740 40.61 6b 25.05 29.73 7 C00-C143 口腔、口咽及下咽 7,111 30.50 20.85 22.47 口腔 4,753 20.39 14.00 15.10 口咽 1,333 5.72 3.90 4.18 下咽 1,025 4.40 2.96 3.18

8 C54 子宮體 1,939 16.65 11.10 11.98 9 C16 胃 3,843 16.48 6a 9.68 11.25 10 C444 皮膚 3,569 15.31 8.87 10.50 C00-C80 全癌症 105,082 450.69 293.90 327.30

10 大癌症死亡率（每 10 萬人口），民國 101 年

順位 ICD-10 原發部位個案數（人）

粗死亡率年齡標準化死亡率 2a

年齡標準化死亡率 2b

1 C33-C34 肺、支氣管及氣管 8,587 36.83 21.31 25.02 2 C22 肝及肝內膽管 8,116 34.81 21.28 24.37 3 C18-C21 結腸、直腸、乙狀結腸連結部及肛門 5,131 22.01 12.32 14.69 4 C50 女性乳房 1,912 16.42 6a 10.53 11.47 5 C00-C143 口腔、口咽及下咽 2,566 11.01 7.36 8.00 6 C16 胃 2,386 10.23 5.70 6.78 7 C61 攝護腺 1,187 10.17 6b 5.17 6.63 8 C15 食道 1,581 6.78 4.44 4.82 9 C25 胰 1,629 6.99 4.13 4.78 10 C53 子宮頸 669 5.75 6a 3.37 3.85 C00-C97 全癌症 43,665 187.28 112.36 129.48

註： 1. 自 96 年癌症登記報告起，淋巴瘤從各部位獨立出來計算發生率，並納入排名。淋巴瘤：ICD-O-3 M-CODE 請見 p.495 附錄五。 2. 年齡標準化率 2a係使用 1976 年世界標準人口為標準人口。年齡標準化率 2b係使用 2000 年世界標準人口為標準人口。 3. 口腔、口咽及下咽原發部位代碼包括 ICD-O-3 & ICD-10：C00-C06、C09-C10、C12-14。細分類代碼請見 p.18。 4. 皮膚原發部位包括基底細胞癌個案。 5. 原位癌：組織形態之分類碼第 5 碼（性態譯碼）為 2。 6. (a)每 10 萬女性人口粗發生率及粗死亡率；(b)每 10 萬男性人口粗發生率及粗死亡率

- 3 -


肺癌發現時⼤大多晚期

- 552 -

肺癌

表十一之三肺癌(非小細胞癌)發生人數按臨床、病理、整併期別＊分類

期別臨床期別病理期別整併期別

申報數 % 申報數 % 申報數 %

合計 9202 100.00 9202 100.00 9202 100.00 0 期 13 0.14 26 0.28 26 0.28 I 期 1698 18.45 1648 17.91 1730 18.80 I I 期 403 4.38 323 3.51 425 4.62 III 期 1485 16.14 452 4.91 1503 16.33 IV 期 5425 58.95 2007 21.81 5491 59.67 不詳 178 1.93 4746 51.58 27 0.29

表十一之四肺癌(小細胞癌)發生人數按臨床、病理、整併期別＊分類


申報數 % 申報數 % 申報數 %

合計 743 100.00 743 100.00 743 100.00 I 期 14 1.88 7 0.94 14 1.88 I I 期 9 1.21 3 0.40 10 1.35 III 期 196 26.38 14 1.88 197 26.51 IV 期 518 69.72 147 19.78 518 69.72 不詳 6 0.81 572 76.99 4 0.54

表十一之五肺癌發生人數按臨床、病理分類

病理期別

0期 I期 II期 III期 IV期合計

臨床期別

0 期 10 2 0 1 0 13 I 期 7 1340 111 100 25 1583 I I 期 0 90 141 53 16 300 III 期 1 118 62 286 31 498 IV 期 0 3 3 4 2070 2080 合計 18 1553 317 444 2142 4474

Kappa=0.7806 註：計算 Kappa值時，排除病理期別、臨床期別不詳者

肺癌⼤大腸癌

- 529 -

結腸癌

表八之一結腸癌發生人數按年齡及性別分類

年齡性別

年齡性別

男性女性合計男性女性合計 00-04歲 0 0 0 45-49歲 207 223 430 05-09歲 0 0 0 50-54歲 405 347 752 10-14歲 3 2 5 55-59歲 607 453 1060 15-19歲 4 4 8 60-64歲 744 488 1232 20-24歲 5 1 6 65-69歲 549 422 971 25-29歲 8 11 19 70-74歲 524 416 940 30-34歲 50 45 95 75-79歲 542 486 1028 35-39歲 61 80 141 80-84歲 447 371 818 40-44歲 102 140 242 85歲以上 290 307 597 合計 4548 3796 8344

表八之二結腸癌發生人數按臨床、病理及整併期別＊分類


申報數 % 申報數 % 申報數 % 合計 8344 100.09 8344 100.09 8344 100.09 0 期 260 3.12 1061 12.72 1069 12.81 I 期 1319 15.90 1353 16.22 1391 16.67 I I 期 1277 15.30 1831 21.94 1867 22.38 III 期 2349 28.15 2090 25.05 2174 26.05 IV 期 1643 19.69 1275 15.28 1760 21.09 不詳 1496 17.93 734 8.80 83 0.99 註：整併期別＊-請參考 101年度臨床與病理期別(AJCC_7th)之整併流程說明，如圖 1所示。

表八之三結腸癌發生人數按臨床、病理分類

病理期別

0期 I期 II期 III期 IV期合計

臨床期別

0 期 213 29 6 3 1 252 I 期 96 701 209 266 6 1278 I I 期 16 121 656 410 32 1235 II I 期 13 159 785 1219 100 2276 IV 期 1 5 28 28 1092 1154 合計 339 1015 1684 1926 1231 6195

Kappa=0.5076 註：計算 Kappa值時，排除病理期別、臨床期別不詳者。

75.09%47.84%


LUNG CANCER SURVIVAL

0%

20%

40%

60%

80%

Ia Ib IIa IIb IIIa IIIb IV

肺癌五年存活率

⺫⽬目前肺癌篩檢

低劑量電腦斷層(LDCT)

吸菸超過30 pack-year

96.4% False Positive

Low-Dose CT Screening

Volume 340 Number 1

·

1

The New England

Journal

of

Medicine

© Copyr ight, 1999, by the Massachusetts Medical Society

VOLUME 340

J

ANUARY

7, 1999

NUMBER 1

A COMPARISON OF TWO ANTIMICROBIAL-IMPREGNATED CENTRAL VENOUS CATHETERS

R

ABIH

O. D

AROUICHE

, M.D., I

SSAM

I. R

AAD

, M.D., S

TEPHEN

O. H

EARD

, M.D., J

OHN

I. T

HORNBY

, P

H

.D., O

LIVIER

C. W

ENKER

, M.D., A

NDREA

G

ABRIELLI

, M.D., J

OHANNES

B

ERG

, M.D., N

ANCY

K

HARDORI

, M.D., H

END

H

ANNA

, M.D., R

AY

H

ACHEM

, M.D., R

ICHARD

L. H

ARRIS

, M.D.,

AND

G

LEN

M

AYHALL

, M.D.,

FOR

THE

C

ATHETER

S

TUDY

G

ROUP

*

A

BSTRACT

Background

The use of central venous cathetersimpregnated with either minocycline and rifampinor chlorhexidine and silver sulfadiazine reduces therates of catheter colonization and catheter-relatedbloodstream infection as compared with the use ofunimpregnated catheters. We compared the ratesof catheter colonization and catheter-related blood-stream infection associated with these two kinds ofantiinfective catheters.

Methods

We conducted a prospective, random-ized clinical trial in 12 university-affiliated hospitals.High-risk adult patients in whom central venouscatheters were expected to remain in place for threeor more days were randomly assigned to undergoinsertion of polyurethane, triple-lumen catheters im-pregnated with either minocycline and rifampin (onboth the luminal and external surfaces) or chlorhex-idine and silver sulfadiazine (on only the externalsurface). After their removal, the tips and subcutane-ous segments of the catheters were cultured by boththe roll-plate and the sonication methods. Peripheral-blood cultures were obtained if clinically indicated.

Results

Of 865 catheters inserted, 738 (85 percent)produced culture results that could be evaluated. Theclinical characteristics of the patients and the risk fac-tors for infection were similar in the two groups.Catheters impregnated with minocycline and rifam-pin were 1/3 as likely to be colonized as catheters im-pregnated with chlorhexidine and silver sulfadiazine(28 of 356 catheters [7.9 percent] vs. 87 of 382 [22.8percent], P<0.001), and catheter-related bloodstreaminfection was 1/12 as likely in catheters impregnatedwith minocycline and rifampin (1 of 356 [0.3 percent],vs. 13 of 382 [3.4 percent] for those impregnated withchlorhexidine and silver sulfadiazine; P<0.002).

Conclusions

The use of central venous cathetersimpregnated with minocycline and rifampin is asso-ciated with a lower rate of infection than the use ofcatheters impregnated with chlorhexidine and silversulfadiazine. (N Engl J Med 1999;340:1-8.)

©1999, Massachusetts Medical Society.

From the Departments of Medicine (R.O.D., R.L.H.), Physical Medi-cine and Rehabilitation (R.O.D.), Family and Community Medicine(J.I.T.), and Anesthesiology (O.C.W.), Baylor College of Medicine and Vet-erans Affairs Medical Center, Houston; the Department of Medical Sub-specialties, University of Texas M.D. Anderson Cancer Center, Houston(I.I.R., H.H., R.H.); the Department of Anesthesiology, University ofMassachusetts Medical Center, Worcester (S.O.H.); the Departments ofSurgery (A.G.) and Medicine (J.B.), University of Florida College of Med-icine, Gainesville; the Department of Medicine, Southern Illinois Univer-sity School of Medicine, Springfield (N.K.); and the Department of Med-icine, University of Texas Medical Branch, Galveston (G.M.). Addressreprint requests to Dr. Darouiche at the Veterans Affairs Medical Center,Infectious Disease Section (Rm. 4B-370), 2002 Holcombe Blvd., Hous-ton, TX 77030, or at [email protected].

*Other members of the Catheter Study Group are listed in the Appendix.

NFECTION associated with the use of centralvenous catheters can result in serious medicalcomplications and expensive care.

1

In prospec-tive, randomized clinical trials, the use of cen-

tral venous catheters impregnated with either mi-nocycline and rifampin

2

or chlorhexidine and silversulfadiazine

3

was associated with reduced rates ofcatheter colonization and catheter-related blood-stream infection, as compared with unimpregnatedcatheters. In vitro studies

4

and studies in animals

5

have suggested that catheters impregnated with mi-nocycline and rifampin can resist infection more ef-fectively than catheters impregnated with chlorhexi-dine and silver sulfadiazine, but the clinical efficacyof these two types of antiinfective catheters has notbeen compared directly. We compared catheters im-pregnated with minocycline and rifampin with thoseimpregnated with chlorhexidine and silver sulfadia-zine in terms of the rates of colonization of cathetersand bloodstream infection.

METHODS

Patients

The trial was conducted between December 1995 and July1997 in 12 university-affiliated hospitals. The study was approvedby the appropriate institutional review boards. Hospitalized adults

I

The New England Journal of Medicine Downloaded from nejm.org at NATIONAL TAIWAN UNIVERSITY on September 25, 2015. For personal use only. No other uses without permission.

Copyright © 1999 Massachusetts Medical Society. All rights reserved.

Red

uced

Lun

g-C

an

cer M

or

tality w

ith Lo

w-D

ose C

T Screen

ing

n en

gl j m

ed 365;5

nejm

.org

au

gu

st 4, 2011401

Table 3. Diagnostic Follow-up of Positive Screening Results in the Three Screening Rounds.*

Variable Low-Dose CT Chest Radiography

T0 T1 T2 Total T0 T1 T2 Total

number (percent)

Total positive tests 7191 (100.0) 6901 (100.0) 4054 (100.0) 18,146 (100.0) 2387 (100.0) 1482 (100.0) 1174 (100.0) 5043 (100.0)

Lung cancer confirmed 270 (3.8) 168 (2.4) 211 (5.2) 649 (3.6) 136 (5.7) 65 (4.4) 78 (6.6) 279 (5.5)

Lung cancer not confirmed† 6921 (96.2) 6733 (97.6) 3843 (94.8) 17,497 (96.4) 2251 (94.3) 1417 (95.6) 1096 (93.4) 4764 (94.5)

Positive screening results with complete diagnos-tic follow-up information

7049 (100.0) 6740 (100.0) 3913 (100.0) 17,702 (100.0) 2348 (100.0) 1456 (100.0) 1149 (100.0) 4953 (100.0)

Any diagnostic follow-up 6369 (90.4) 3866 (57.4) 2522 (64.5) 12,757 (72.1) 2176 (92.7) 1078 (74.0) 957 (83.3) 4211 (85.0)

Clinical procedure 5089 (72.2) 3190 (47.3) 2151 (55.0) 10,430 (58.9) 1414 (60.2) 723 (49.7) 658 (57.3) 2795 (56.4)

Imaging examination 5717 (81.1) 2520 (37.4) 2009 (51.3) 10,246 (57.9) 2010 (85.6) 968 (66.5) 906 (78.9) 3884 (78.4)

Chest radiography 1284 (18.2) 613 (9.1) 650 (16.6) 2,547 (14.4) 867 (36.9) 381 (26.2) 365 (31.8) 1613 (32.6)

Chest CT 5153 (73.1) 2046 (30.4) 1608 (41.1) 8,807 (49.8) 1546 (65.8) 745 (51.2) 712 (62.0) 3003 (60.6)

FDG PET or FDG PET–CT 728 (10.3) 350 (5.2) 393 (10.0) 1,471 (8.3) 179 (7.6) 105 (7.2) 113 (9.8) 397 (8.0)

Percutaneous cytologic examination or biopsy

155 (2.2) 74 (1.1) 93 (2.4) 322 (1.8) 83 (3.5) 37 (2.5) 52 (4.5) 172 (3.5)

Transthoracic 120 (1.7) 60 (0.9) 74 (1.9) 254 (1.4) 67 (2.9) 31 (2.1) 43 (3.7) 141 (2.8)

Extrathoracic 39 (0.6) 17 (0.3) 24 (0.6) 80 (0.5) 20 (0.9) 6 (0.4) 13 (1.1) 39 (0.8)

Bronchoscopy 306 (4.3) 178 (2.6) 187 (4.8) 671 (3.8) 107 (4.6) 56 (3.8) 62 (5.4) 225 (4.5)

With neither biopsy nor cytologic testing 126 (1.8) 95 (1.4) 99 (2.5) 320 (1.8) 45 (1.9) 19 (1.3) 32 (2.8) 96 (1.9)

With biopsy or cytologic testing 194 (2.8) 95 (1.4) 102 (2.6) 391 (2.2) 74 (3.2) 40 (2.7) 36 (3.1) 150 (3.0)

Surgical procedure 297 (4.2) 197 (2.9) 219 (5.6) 713 (4.0) 121 (5.2) 51 (3.5) 67 (5.8) 239 (4.8)

Mediastinoscopy or mediastinotomy 60 (0.9) 32 (0.5) 25 (0.6) 117 (0.7) 22 (0.9) 12 (0.8) 21 (1.8) 55 (1.1)

Thoracoscopy 82 (1.2) 56 (0.8) 96 (2.5) 234 (1.3) 22 (0.9) 11 (0.8) 20 (1.7) 53 (1.1)

Thoracotomy 197 (2.8) 148 (2.2) 164 (4.2) 509 (2.9) 96 (4.1) 44 (3.0) 44 (3.8) 184 (3.7)

Other procedures 168 (2.4) 96 (1.4) 63 (1.6) 327 (1.8) 55 (2.3) 33 (2.3) 34 (3.0) 122 (2.5)

* The screenings were performed at 1-year intervals, with the first screening (T0) performed soon after the time of randomization. FDG PET denotes 18F-fluorodeoxyglucose positron-emission tomography.

† Positive tests with incomplete information on diagnostic follow-up are included in this category (142 at T0, 161 at T1, and 141 at T2 in the low-dose CT group and 39 at T0, 26 at T1, and 25 at T2 in the radiography group).

The New

England Journal of Medicine

Dow

nloaded from nejm

.org at NA

TION

AL TA

IWA

N U

NIV

ERSITY on D

ecember 21, 2015. For personal use only. N

o other uses without perm

ission. Copyright ©

2011 Massachusetts M

edical Society. All rights reserved.

Red

uced

Lun

g-C

ancer

Mo

rtality w

ith Lo

w-D

ose C

T Screen

ing

n en

gl j m

ed 365;5

nejm

.org

au

gu

st 4, 2011401

Table 3. Diagnostic Follow-up of Positive Screening Results in the Three Screening Rounds.*

Variable Low-Dose CT Chest Radiography

T0 T1 T2 Total T0 T1 T2 Total

number (percent)

Total positive tests 7191 (100.0) 6901 (100.0) 4054 (100.0) 18,146 (100.0) 2387 (100.0) 1482 (100.0) 1174 (100.0) 5043 (100.0)

Lung cancer confirmed 270 (3.8) 168 (2.4) 211 (5.2) 649 (3.6) 136 (5.7) 65 (4.4) 78 (6.6) 279 (5.5)

Lung cancer not confirmed† 6921 (96.2) 6733 (97.6) 3843 (94.8) 17,497 (96.4) 2251 (94.3) 1417 (95.6) 1096 (93.4) 4764 (94.5)

Positive screening results with complete diagnos-tic follow-up information

7049 (100.0) 6740 (100.0) 3913 (100.0) 17,702 (100.0) 2348 (100.0) 1456 (100.0) 1149 (100.0) 4953 (100.0)

Any diagnostic follow-up 6369 (90.4) 3866 (57.4) 2522 (64.5) 12,757 (72.1) 2176 (92.7) 1078 (74.0) 957 (83.3) 4211 (85.0)

Clinical procedure 5089 (72.2) 3190 (47.3) 2151 (55.0) 10,430 (58.9) 1414 (60.2) 723 (49.7) 658 (57.3) 2795 (56.4)

Imaging examination 5717 (81.1) 2520 (37.4) 2009 (51.3) 10,246 (57.9) 2010 (85.6) 968 (66.5) 906 (78.9) 3884 (78.4)

Chest radiography 1284 (18.2) 613 (9.1) 650 (16.6) 2,547 (14.4) 867 (36.9) 381 (26.2) 365 (31.8) 1613 (32.6)

Chest CT 5153 (73.1) 2046 (30.4) 1608 (41.1) 8,807 (49.8) 1546 (65.8) 745 (51.2) 712 (62.0) 3003 (60.6)

FDG PET or FDG PET–CT 728 (10.3) 350 (5.2) 393 (10.0) 1,471 (8.3) 179 (7.6) 105 (7.2) 113 (9.8) 397 (8.0)

Percutaneous cytologic examination or biopsy

155 (2.2) 74 (1.1) 93 (2.4) 322 (1.8) 83 (3.5) 37 (2.5) 52 (4.5) 172 (3.5)

Transthoracic 120 (1.7) 60 (0.9) 74 (1.9) 254 (1.4) 67 (2.9) 31 (2.1) 43 (3.7) 141 (2.8)

Extrathoracic 39 (0.6) 17 (0.3) 24 (0.6) 80 (0.5) 20 (0.9) 6 (0.4) 13 (1.1) 39 (0.8)

Bronchoscopy 306 (4.3) 178 (2.6) 187 (4.8) 671 (3.8) 107 (4.6) 56 (3.8) 62 (5.4) 225 (4.5)

With neither biopsy nor cytologic testing 126 (1.8) 95 (1.4) 99 (2.5) 320 (1.8) 45 (1.9) 19 (1.3) 32 (2.8) 96 (1.9)

With biopsy or cytologic testing 194 (2.8) 95 (1.4) 102 (2.6) 391 (2.2) 74 (3.2) 40 (2.7) 36 (3.1) 150 (3.0)

Surgical procedure 297 (4.2) 197 (2.9) 219 (5.6) 713 (4.0) 121 (5.2) 51 (3.5) 67 (5.8) 239 (4.8)

Mediastinoscopy or mediastinotomy 60 (0.9) 32 (0.5) 25 (0.6) 117 (0.7) 22 (0.9) 12 (0.8) 21 (1.8) 55 (1.1)

Thoracoscopy 82 (1.2) 56 (0.8) 96 (2.5) 234 (1.3) 22 (0.9) 11 (0.8) 20 (1.7) 53 (1.1)

Thoracotomy 197 (2.8) 148 (2.2) 164 (4.2) 509 (2.9) 96 (4.1) 44 (3.0) 44 (3.8) 184 (3.7)

Other procedures 168 (2.4) 96 (1.4) 63 (1.6) 327 (1.8) 55 (2.3) 33 (2.3) 34 (3.0) 122 (2.5)

* The screenings were performed at 1-year intervals, with the first screening (T0) performed soon after the time of randomization. FDG PET denotes 18F-fluorodeoxyglucose positron-emission tomography.

† Positive tests with incomplete information on diagnostic follow-up are included in this category (142 at T0, 161 at T1, and 141 at T2 in the low-dose CT group and 39 at T0, 26 at T1, and 25 at T2 in the radiography group).

The New

England Journal of Medicine

Dow

nloaded from nejm

.org at NA

TION

AL TA

IWA

N U

NIV

ERSITY on D

ecember 21, 2015. For personal use only. N

o other uses without perm

ission. Copyright ©

2011 Massachusetts M

edical Society. All rights reserved.

Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic

Screening

National Lung Screening Trial Research Team et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. The New England Journal of Medicine 365, 395–409 (2011).

低劑量電腦斷層(LDCT)陽性

需要侵⼊入性檢查11%

侵⼊入性檢查併發⽐比例超過20%Pneumothroax, pulmonary hemorrhage, haemothroax, tumor seeding, cardiac tamponade, infection, empyema, pulmonary venous air embolism, and Mortality 死亡率 0.15-0.47%

陳定南

肺腺癌第三期

1943-2006

單國璽

肺腺癌第四期

1923-2012

–設計對⽩白

“感謝天主，早期發現肺癌並切除。我現在還活

的好好的。”陳建仁

肺腺癌第一期

1951-

肺功能部分永久喪失

當肺腺癌擴散時像被掐住了脖子，沒辦法呼吸

你知道得肺癌多悽慘？當肺腺癌擴散出去會喘的時候，甚至到肺癌末期會吸不到空氣，那種感覺就像是有人掐著你的脖子，那是一種很可怕的感覺。人的肺切掉就沒辦法再生，如果一個肺腺癌患者又復發的話，一個人有多少的肺可以割？

陳佩琪告白

難以早期發現

缺少良好篩檢工具

癌症切除後肺活量減少

肺癌：寂靜的殺手

1. 肺癌：寂靜殺⼿手2. 暴露致癌物引起基因突變，基因突變導致癌症

3. ⾎血液 cfDNA 帶有基因突變4. EGFR基因突變警⽰示肺癌罹患⾵風險5. EGFR基因突變輔助肺癌篩檢

Although both genetic and environmental factors contribute to

the development of cancer, environmental influences

appear to be the dominant risk factors for most

cancers.

C H A P T E R

7 Neoplasia

NeoplasiaRobbins and CotranPATHOLOGICBASIS OF DISEASE NINTH EDTION

C H A P T E R

7 Neoplasia


癌症的危險因子

主要來自後天環境

WHO認定空氣中的致癌物：肺癌

• 微塵 PM 2.5• ⽯石棉 Asbestos• 氡 Radon• ⾹香煙 Smoking (second hand) • 甲醛 Formaldehyde• 多環芳⾹香烴Polycyclic aromatic hydrocarbons: 如苯、苯並[a]芘

(B[a]P) • 柴油引擎廢氣 Diesel engine exhaust • 燃燒煤和⽊木材產⽣生之煙霧• 揮發性有機物(Volatile organic compounds, VOC)：如氯⼄乙烯(vinyl

chloride monomer, VCM)、四氯⼄乙烯、三氯⼄乙烯(trichloroethylene)

Nonlethal genetic damage lies at the heart of carcinogenesis.

The initial damage (or mutation) may be caused by environmental exposures, may be inherited in the germline, or may be spontaneous and random, falling into the category of “bad luck.” The term environmental, used in this context, refers to any acquired mutation caused by exogenous agents, such as viruses or environmental chemicals, or by endogenous products of cellular metabolism.

A tumor is formed by the clonal expansion of a single precursor cell that has incurred genetic damage (i.e., tumors are clonal).

Figure 7-22 Development of a cancer through stepwise acquisition of complementary mutations. The order in which various driver mutations occur in initiated precursor cells is not known and may vary from tumor to tumor. See text for details.

Initiating mutation

Normalcell

Carcinogen-inducedmutation

Mutation affectinggenomic integrity

Additional drivermutations

Additional mutations,Emergence of subclones

Accumulation of driver andpassenger mutations

Diagnosis

Initiated precursor withstem cell-like properties

Precursor withmutator phenotype

Foundingcancer cell

Geneticallyheterogeneous

cancerAcquisition of

genomic instabilityAcquisition of

cancer hallmarksFurther genetic

evolution

C H A P T E R

7 Neoplasia


Alterations in DNA are heritable, being passed to daughter cells, and thus all cells within an individual tumor share the same set of mutations that were present at the moment of transformation. Such tumor-specific mutations are most often identified by DNA sequencing

Carcinogenesis results from the accumulation of complementary mutations in a stepwise fashion over time (Fig. 7-22).

The notion that malignant tumors arise from a protracted sequence of events is supported by epidemiological, experimental, and molecular studies, and the study of oncogenes and tumor suppressor genes has provided a firm molecular footing for the concept of multistep carcinogenesis. Genome-wide sequencing of cancers has revealed as few as ten or so mutations in certain leukemias to many thousands of mutations in tumors that arise following chronic exposure to carcinogens, such as lung cancers associated with cigarette smoking. Although the presence of multiple mutations is consistent with the idea that no single mutation will suffice to produce a cancer. Many of these cancers evolve through a series of morphologically identifiable stages: colon epithelial hyperplasia followed by formation of adenomas that progressively enlarge and ultimately undergo malignant transformation. Molecular analyses of proliferations at each of these stages have indeed shown that precancerous lesions have fewer mutations than adenocarcinomas and suggest a tendency to acquire particular mutations in the sequence illustrated in Figure 7-42 (next page). According to this scheme, inactivation of the APC tumor suppressor gene occurs first, followed by activation of RAS and, ultimately, loss of a tumor suppressor gene on 18q and loss of TP53.

Genetic mutations cause cancers and are identified by DNA sequencing.

C H A P T E R

7 Neoplasia


1. Nonlethal genetic damage lies at the heart of carcinogenesis.

2. A tumor is formed by the clonal expansion of a single precursor cell that has incurred genetic damage (i.e., tumors are clonal).

3. Carcinogenesis results from the accumulation of complementary mutations in a stepwise fashion over time.


Initiating mutation

Normalcell






Diagnosis



Foundingcancer cell





evolution

CarcinogenExposure

Apoptosis

Nonlethal damage

Senescence Successful repair

ApoptosisCancer cells

Normalcell

Damaged cell

Metabolicactivation

Additional mutationsProliferation

Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE

Cell proliferation:Altered differentiation

Permanent DNA lesion:Initiated cell

Binding to DNA:Adduct formation

Electrophilicintermediates

Detoxification

DetoxificationIN

ITIA

TIO

NDNArepair

Celldeath

PRO

MO

TIO

N

Excretion

Carcinogen to

Cancer Step by Step

持續出現突變DNA

短暫出現突變DNA

Driver Mutation &

Passenger mutation

Who done it? 誰是真兇?

MucosaSubmucosaMuscularis

propria

APC at 5q21 APCβ-catenin

K-RASat 12p12

TP53 at 17p13LOH at 18q21

(SMAD 2 and 4)

Wild-typeTP53

TelomeraseMany other genes

Germ-line (inherited) or somatic (acquired) mutations of cancer suppressor genes ("first hit")

Methylation abnormalitiesInactivation of normal alleles ("second hit")

Proto-oncogene mutations

Homozygous loss of additional cancer suppressor genes Additional mutations

Gross chromosomal alterations

Oncogene-inducedsenescence

NORMALCOLON

MUCOSAAT RISK

ADENOMAS

CARCINOMA

致癌突變Driver mutationex: EGFR T790M

路⼈人甲突變Passenger mutation

致癌物 Carcinogen soil

致癌物暴露，累積基因突變

累積基因突變導致癌症

基因定序可發現基因突變

1. 肺癌：寂靜殺⼿手2. 暴露致癌物引起基因突變，基因突變導致癌症3. ⾎血液 cfDNA 帶有基因突變

4. EGFR基因突變警⽰示肺癌罹患⾵風險5. EGFR基因突變輔助肺癌篩檢

癌細胞

⾎血液

cf DNA

Credit: AstraZeneca® Iressa® Official Page 阿斯特捷利康®⼤大藥廠肺癌標靶藥艾瑞莎®官⽅方網站

癌細胞釋出DNA⽚片段到⾎血液中

循環游離DNAcf DNA

只要管⾎血液簡便無侵⼊入⾵風險

3 CloDiA technology

超過 % 偵測突變正確率更靈敏、更專⼀一

92

阿斯特捷利康 AstraZeneca ⼤大藥廠肺癌標靶藥物仿單艾瑞莎 IRESSA ⽤用藥前

使⽤用 cf DNA 檢測基因突變®

http://www.astrazeneca.com/Media/Press-releases/Article/20142609--iressa-receives-chmp-positive-opinion-to-include-blood-based-diagnostic-testing-in-european-label

癌前突變異常增⽣生

原位癌癌

早期晚期

治療⼿手術化療放療

微量殘餘癌症

復發

PremalignantCIS

Carcinoma in situ

CancerTreatment

Minimal Residual Disease

Relapse

癌細胞量

致癌基因突變量


原位癌

PremalignantCIS

Carcinoma in situ

癌早期晚期

Cancer

早期突變基因

濃度低

偵測⽅方法

必須敏感

cf DNA 突變所需濃度

qPCR NGS

ddPCR BEAMing CloDiA PCR

偵測

1991 2002

2006 20092012

DNA濃度需要2-5%以上

DNA濃度0.01-0.1%即可

細菌E coli.

病毒SARS

檢驗方法夠靈敏

血液中看得到

DNA突變

⽤用這個新⽅方法⼀一定可以逮到莫⾥里亞蒂教授

1. 肺癌：寂靜殺⼿手2. 暴露致癌物引起基因突變，基因突變導致癌症3. ⾎血液cfDNA 帶有基因突變4. EGFR基因突變警⽰示肺癌罹患⾵風險

5. EGFR基因突變輔助肺癌篩檢

突變細胞

cf DNA

CloDiA PCR

異常組織 (Hyperplasia, Dysplasia)

腫瘤 (原發、轉移、殘餘)

帶有基因突變

突變細胞 cf DNA

異常增⽣生組織 cf DNA

腫瘤 cf DNA (ct DNA)

(noise cancellation)

Sanger Sequencing (Golden standard)

篩檢/⾵風險評估診斷預後選擇治療監測癌症


原位癌癌

早期晚期


微量殘餘癌症

復發

PremalignantCIS

Carcinoma in situ

CancerTreatment


Relapse

癌化細胞量


cf DNA 突變所需濃度

qPCR NGS

ddPCR BEAMing CloDiA PCR

偵測

1991 2002

2006 20092012

DNA濃度需要2-5%以上

DNA濃度0.01-0.1%即可

偵測 EGFR 突變超靈敏• EGFR Exon 19 0.01-0.1%

• del

• EGFR Exon 21 0.1-1%

• L858R

Acknowledge ⼯工業技術研究院測試

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

DetoxificationIN

ITIA

TIO

NDNArepair

Celldeath

PRO

MO

TIO

N

Excretion

Carcinogen to

Cancer Step by Step

癌化細胞株持續釋出突變DNA到⾎血液中

短暫釋出突變DNA到⾎血液中

VV

Gene 汙染物誘發癌症突變點

KRAS VCMs Liver Angiosarcoma Codon 12, 13

KRAS PAH, PM 2.5 Lung Cancer Codon 12, 13

p53 PAHs Lung Cancer Codon 273

EGFR PAHs, PM 2.5 Lung Cancer Exon19, Exon 20, Exon 21

JAK2 Radiation, VOCs (benzene)

Leukemia (MF) V617

VCM (Vinyl chloride monomer)氯⼄乙烯單體; PAH(Polycyclic aromatic hydrocarbons)多環芳⾹香烴; VOC(Volatile organic compounds)揮發性有機物; MF: Myelofibrosis

空氣汙染造成的基因突變

KRAS Tp53EGFR

JAK2

肺癌 EGFR 突變亞洲⼈人種肺癌，常⾒見EGFR突變，⾼高達40-50%

Biomolecules 2015, 5, 2464-2476

EGFR突變常見於亞洲不煙女性

鳳飛飛1953-2012

肺癌

吸菸一年

EGFR突變機會增加

500%

Shigematsu H, Gazdar AF. Somatic mutations of epidermal growth factor receptor signaling pathway in lung cancers. International Journal of Cancer 2006;118(2):257–62.

⾹香腸福⾺馬林病理標本

⼤大腸切除

8% 陽性病理科內技術員抽⾎血檢驗EGFR 突變

病理科主任：是什麼造成EGFR 突變？

⼤大腸切除

福⾺馬林（甲醛）病理標本

連續的⾼高危險突變Low does CT追蹤後：未發現病灶

ALL CLEAR!

Case 1: Transient Exposure to Carcinogen (Passenger Mutation)

TEST 1 2 3 4 5 6 7 8 9 10

EGFR Exon 19

EGFR Exon 20

EGFR Exon 21

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion

短暫接觸到致癌物，造成路⼈人甲突變(passenger mutation)，停

⽌止接觸後就恢復正常

Case 1: Transient Exposure to Carcinogen (Driver Mutation)

TEST 1 2 3 4 5 6 7 8 9 10

EGFR Exon 19

EGFR Exon 20

EGFR Exon 21 L858R L858R

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion

接觸到致癌物，造成路⼈人甲突變(passenger mutation)和致癌突變，癌化細胞株短暫出現，停⽌止接觸後，免疫系統清除癌化細胞株，終於恢復正常

Case 3: Persistent Exposure to Carcinogen (Transient Driver Mutation)

TEST 1 2 3 4 5 6 7 8 9 10

EGFR Exon 19

EGFR Exon 20

EGFR Exon 21 L858R L858R L858R L858R

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion

接觸到致癌物，造成路⼈人甲突變(passenger mutation)和致癌突變，也形成癌化細胞株，雖然被免疫系統清除，但是持續暴露還是再度造成致癌突變

Progression/Regression of cervical CIN

Regression Persistence Progression to CIS

Progression to invasive

cancer

CIN1 57% 32% 11% 1%CIN2 43% 35% 5% 5%CIN3 32% <56% - >12%

Resolution of CIN1 in adolescent is 90%McCredie MR, Sharples KJ, Paul C, et al. Natural history of cervical neoplasia and risk of invasive cancer in women with cervical intraepithelial neoplasia 3: a retrospective cohort study. The Lancet Oncology 2008;9(5):425–34.

早期偵測基因突變

及早發現及早介入EGFR

1. 肺癌：寂靜殺⼿手2. 暴露致癌物引起基因突變，基因突變導致癌症3. ⾎血液cfDNA 帶有基因突變4. EGFR基因突變警⽰示肺癌罹患⾵風險5. EGFR基因突變輔助肺癌篩檢


原位癌癌

早期晚期


微量殘餘癌症

復發

PremalignantCIS

Carcinoma in situ

CancerTreatment


Relapse

癌細胞量


C H A P T E R

7 Neoplasia


1. Nonlethal genetic damage lies at the heart of carcinogenesis.

2. A tumor is formed by the clonal expansion of a single precursor cell that has incurred genetic damage (i.e., tumors are clonal).

3. Carcinogenesis results from the accumulation of complementary mutations in a stepwise fashion over time.


Initiating mutation

Normalcell






Diagnosis



Foundingcancer cell





evolution

致癌突變Driver mutationex: EGFR T790M

路⼈人甲突變Passenger mutation

衍⽣生突變Derivative mutation

致癌物 Carcinogen soil

Case 4: Cancer Progression

TEST 1 2 3 4 5 6 7 8 9 10

EGFR Exon 19 del 19 del 19 del 19

EGFR Exon 20 T790M T790M

EGFR Exon 21 L858R L858R L858R L858R L858R L858R L858R L858R

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion

Case 4: Cancer Progression

TEST 1 2 3 4 5 6 7 8 9 10

EGFR Exon 19 del 19 del 19 del 19

EGFR Exon 20 T790M T790M

EGFR Exon 21 L858R L858R L858R L858R L858R L858R L858R L858R

Initiating mutation (Ubiquitous)

癌化啟始突變(存在於所有癌細胞，到處存在)

NA

TUR

E MED

ICIN

E VO

LUM

E 14 | NU

MB

ER 9 | SEPTEM

BER

2008 9

87

Table 1 ctDNA in subjects before and after surgeryctDNA level (ctDNA molecules in 2 ml)a CEA level (ng ml–1)

Subject number

Stage Surgery number

Surgical procedure Resection Gene Pre-surgery day 0

Post-operative day 1

Post-operative days 2–10

Post-operative follow-up

days 13–56

Pre-surgery day 0

Post-operative day 1

Post-operative days 2–10

Post-operative follow-up

days 13–56

Disease recurrence

1 IV 1Hepatic metastectomy Complete

APC 99 ± 38 4.0 ± 2.0 0.9 ± 0.3 16 ± 2.369 53 24 22 Yes

KRAS 79 ± 35 2.6 ± 1.3 Neg 5.6 ± 0.9

2 IV 1 Hepatic metastectomy (first-stage)

Incomplete APC 2,951 ± 773 1,336 ± 408 1,508 ± 156 1,049 ± 254 22 14 10 12 Yes

3 IV 1 Right hemicolectomy with hepatic metastectomy

IncompleteAPC 58 ± 18 421 ± 85 404 ± 121 166 ± 63

6.8 7.2 6.5 12 YesKRAS 46 ± 15 485 ± 98 393 ± 118 136 ± 51

4 IV 1 Hepatic metastectomy with RFA

CompleteAPC 16 ± 4 Neg Neg Neg

1.6 1.4 0.8 1.8 NoKRAS 15 ± 4 Neg Neg Neg

5 IV 1Hepatic metastectomy Complete

PIK3CA 213 ± 90 4.9 ± 2.1 7.7 ± 2.3 9.8 ± 3.89.4 6.8 4.4 2.1 Yes

TP53 275 ± 116 4.5 ± 2.0 2.6 ± 0.8 5.7 ± 1.7

6 IV 1 Pulmonary and hepatic metastectomy

CompleteAPC 3,650 ± 1,313 1.3 ± 0.4 3.3 ± 1.3 2.2 ± 0.6

422 149 61 7.2 YesKRAS 2,375 ± 917 1.2 ± 0.5 4.4 ± 1.7 1.2 ± 0.4


Complete KRAS 856 ± 394 117 ± 24 – 220 ± 9 5.3 2.7 – 3.4 Yes

8 IV 1 Sigmoid colectomy with hepatic metastectomy (first-stage)

IncompletePIK3CA 2,575 ± 1,027 1,370 ± 551 6,459 ± 2,305 1,420 ± 408

4.5 2.4 1.6 3.8 YesTP53 2,352 ± 937 802 ± 248 4,171 ± 1,484 944 ± 258

2Right hepatectomy Complete

PIK3CA 644 ± 281 26.5 ± 7.9 3.7 ± 1.2 0.9 ± 0.11.4 0.6 0.5 0.7 Yes

TP53 389 ± 169 5.9 ± 1.7 Neg Neg

9 IV 1 Right hepatectomy Complete TP53 91 ± 33 2.6 ± 3.3 1.2 ± 1.3 Neg 4.4 1.1 0.7 0.5 No

10 IV 1 Right hemicolectomy with hepatic metastectomy

CompleteAPC 6 ± 1.6 Neg Neg Neg

0.9 0.8 0.7 1.2 YesKRAS 3 ± 1.0 Neg 2.4 ± 0.5 1.5 ± 0.7

2 Hepatic metastectomy with RFA

CompleteAPC 128 ± 34 37 ± 14 – 316 ± 64

2.0 0.9 – 1.8 YesKRAS 42 ± 13 11 ± 5 – 131 ± 32

11 IV 1 Sigmoid colectomy with hepatic metastectomy with RFA

Incomplete TP53 14 ± 3 59 ± 22 – 295 ± 71 93 55 – 32 Yes

2 Hepatic metastectomy Complete TP53 2,713 ± 775 10 ± 5 14 ± 7 1.8 ± 0.4 74 43 22 2.8 Yes

3 RFA to hepatic metastases Complete TP53 1,267 ± 243 465 ± 8 – 39 ± 2 52 44 – 9.1 Yes


Incomplete KRAS 28 ± 8 67 ± 9 27 ± 9 120 ± 42 1.6 0.8 0.8 0.7 Yes

13 IV 1 Hepatic metastectomy with partial gastrectomy and omentectomy

Complete APC 1 ± 0.3 1.2 ± 0.9 – – 2.0 1.5 – – Yes

14 II 1 Sigmoid colectomy Complete APC 2 ± 0.7 Neg Neg Neg 3.9 2.7 1.7 1.3 No

15 IV 1 Right hepatectomy Complete KRAS 519 ± 125 612 ± 60 35 ± 11 20 ± 4 17 14 11 4.5 Yes

16 III 1Sigmoid colectomy Complete

APC 5 ± 1.7 – 3.5 ± 0.9 Neg<0.5 <0.5 <0.5 <0.5 No

TP53 2 ± 0.6 – 1.6 ± 0.2 Neg

17 IV 1Right hepatectomy Complete

APC 20,144 ± 5,504 58 ± 22 13 ± 3 –25 17 0.8 – Yes

KRAS 17,482 ± 4,777 97 ± 36 108 ± 27 –

18 IV 1 Hepatic metastectomy Complete APC 29 ± 8 4 ± 1.28 – 0.7 ± 0.4 24 16 – 2.2 NoactDNA level s.d. RFA, radiofrequency ablation; APC, adenomatous polyposis coli; KRAS, Kirsten rat sarcoma viral oncogene homolog; PIK3CA; phosphoinositide-3-kinase, catalytic, polypeptide; TP53, tumor protein p53; Neg, undetectable ctDNA; –, plasma sample not collected.

TE

CH

NIC

AL

RE

PO

RT

S© 2008 Nature Publishing Group http://www.nature.com/naturemedicine

Diehl F, Schmidt K, Choti MA, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med 2008;14(9):985–90.

Basementmembrane

TransformedcellPRIMARY

TUMOR

Extracellularmatrix

METASTATICTUMOR

Hostlymphocyte

Platelets

Clonal expansion,growth, diversification,

angiogenesis

Metastatic subclone

Adhesion to andinvasion of basement

membrane

Passage throughextracellular matrix

Intravasation

Interaction with hostlymphoid cells

Tumor cellembolus

Adhesion tobasementmembrane

Extravasation

Metastaticdeposit

Angiogenesis

Growth

從癌前期到癌後期都可以藉由

反覆出現的基因突變追蹤體內癌細胞株了解體內癌症進展

Initiating mutation (Ubiquitous)

癌化啟始突變(存在於所有癌細胞，到處存在)

Lung biopsy 併發症

⾼高達以上 20%

低劑量電腦斷層(LDCT)陽性

Wu CC, Maher MM, Shepard J-AO. Complications of CT-Guided Percutaneous Needle Biopsy of the Chest: Prevention and Management. American Journal of Roentgenology 2012;196(6):W678–82.

OR

抽胸⽔水抽⾎血

EGFR mutation+

Complication Rate

< 4% < 0.1%

同一位置突變反覆出現

警示體內存在癌細胞株

chemotherapy

Clonal fractions at initial diagnosis Day 170 First relapse

Driver mutation(s) Driver mutation

12.74%

29.04%

5.1%

53.12%

Normal cells

Summary

•‧ 空汙引發啟始肺癌的基因突變

•‧ 僅需抽血，可以早期準確檢驗

啟始肺癌的EGFR基因突變

•‧ 僅需抽血，準確輔助篩檢肺癌

癌症潛藏在你我體內

我們的身體隨時都會產生

不健全的細胞

這就是腫瘤生成的原因

Thank you!Leukemia JAK2/DMNT3A TET2 ASXL1

Colon polyp PIK3CA/BRAFLung EGFR

In total, from the 15 PIK3CA mutations identified inprimary tumors by ddPCR, 14 PIK3CA mutations weredetected in 13of the presurgery plasma samples, as 1patient(patient 4) had concurrent E545K and H1047R mutationsidentified in both tumor and ptDNA. Of these PIK3CA-positive ptDNA samples, 8 patients, including patient 4,had stage IA disease with mutant PIK3CA ptDNA fractionalabundance ranging from 0.01% to 0.12%. Three patientswith stage IIA disease had plasma PIK3CA mutation levelswith a fractional abundance of 0.02%and0.01%,whereas 2stage IIB patients’ plasma samples demonstrated mutantPIK3CA at 0.01% and 2.99% fractional abundance. Frac-tional abundance for all ddPCR results are shown in Tables2 and 3 with 95% CIs in Supplementary Table S4. Repre-sentative ddPCR presurgery plasma DNA analyses areshown in Supplementary Fig. S1.

PIK3CA mutations detected in ptDNA by ddPCR aftersurgery

We then sought to determine whether any patients con-tinued to have detectable mutant PIK3CA after breast sur-gery. Postsurgical plasma specimens were collected from 17of the 29 patients, including 9 patients with a positivemutant PIK3CA presurgical ptDNA sample, and a 10thpatient (patient 4) whose tumor and presurgical ptDNAharbored both E545K andH1047R PIK3CAmutations for atotal of 10 potentially informative samples with 11 muta-tions identified in presurgery ptDNA. We collected post-surgery blood samples within 14 days after surgery in 5 ofthese patients as initially planned, whereas logistical issuesallowed us to collect the remaining 5 patients’ postsurgeryblood at times ranging from15 to 72 days after surgery. Twopatients, patients 16 and 22, had their blood collectedwhile

Table 2. Analysis of PIK3CA mutations in tumors and blood

PatientSequencing FFPEtumor tissue

ddPCR FFPEtumor tissue

ddPCR presurgeryplasma

1 Wild type H1047R (9.4%) H1047R (0.03%)2 Wild type Wild type Wild type3 Wild type Wild type Wild type4 Wild type E545K (28.9%) E545K (0.01%)

H1047R (6%) H1047R (0.02%)5 H1047R H1047R (25.5%) H1047R (0.02%)6 Wild type Wild type Wild type7 Wild type Wild type Wild type8 H1047R H1047R (26%) H1047R (0.12%)9 E545K E545K (43.7%) E545K (0.02%)10 Wild type Wild type Wild type11 H1047R H1047R (13.8%) H1047R (0.01%)12 Wild type Wild type Wild type13 Wild type E545K (16.1%) Wild type14 R:Wild type Wild type Wild type

L:Wild type Wild type Wild type15 Wild type Wild type Wild type16 H1047R H1047R (32.2%) H1047R (2.99%)17 E545K E545K (55.6%) E545K (0.07%)18 Wild type Wild type Wild type19 E545K E545K (20.3%) E545K (0.01%)20 Wild type Wild type Wild type21 Wild type Wild type Wild type22 H1047R H1047R (28.9%) H1047R (0.02%)23 Wild type Wild type Wild type24 Wild type Wild type Wild type25 H1047R H1047R (30.5%) H1047R (0.01%)26 Wild type Wild type Wild type27 Wild type Wild type Wild type28 Wild type H1047R (9.5%) H1047R (0.02%)29 H1047R H1047R (43.1%) H1047R (0.01%)

NOTE: Tumor and blood samples from 29 patients with early-stage breast cancer were analyzed for PIK3CAmutations using Sangersequencing FFPE tumor tissue, ddPCR of FFPE tumors (ddPCR FFPE tumor tissue) and presurgery plasma DNA (ddPCR presurgeryplasma). Percentage reflects fractional abundance of mutant PIK3CA (E545K or H1047R) to total PIK3CA DNA.

Detecting Plasma Tumor DNA in Early-Stage Breast Cancer

www.aacrjournals.org Clin Cancer Res; 20(10) May 15, 2014 2647

on August 30, 2015. © 2014 American Association for Cancer Research. clincancerres.aacrjournals.org Downloaded from

Published OnlineFirst February 6, 2014; DOI: 10.1158/1078-0432.CCR-13-2933

Beaver, J. A. et al. Detection of cancer DNA in plasma of patients with early-stage breast cancer. Clinical Cancer Research 20, 2643–2650 (2014). IF=8.2

Insensitive method

10% 規格

Sensitive method

0.1% 規格

identified 2 additional PIK3CAH1047R mutations, 1 addi-tional PIK3CA E545K mutation and 1 sample with bothH1047R and E545K mutations. The prevalence of PIK3CAmutations detected per tumor by ddPCR was 46.7% (14 of30). Results comparing the FFPE and ddPCR analyses withfractional abundance are shown in Table 2.

PIK3CAmutations detected in ptDNA by ddPCR beforesurgery

Matched presurgery plasma samples were collected for allpatients (n ¼ 29). The amount of total plasma DNA variedamong samples ranging from 3.07 to 22.60 nanograms,which is consistent with prior reports (26–29). These pre-surgery plasma samples were analyzed for PIK3CA E545Kand H1047R mutations using ddPCR for detection. ddPCRdetected 4 patients with PIK3CA exon 9 mutations in theirpresurgery ptDNA with a fractional mutation abundanceranging from 0.01% to 0.07%. Ten presurgery plasma

samples were also identified as harboring a PIK3CAH1047R mutation with a fractional abundance rangingfrom 0.01% to 2.99%. Comparison of the ddPCR ptDNAresults with corresponding ddPCR FFPE samples demon-strated that of the 15 PIK3CA mutations detected in tissuesamples, identical mutations were detected in 14 of thematched ptDNA samples (Table 2). Notably, the singlepatient (patient 13) in whom the PIK3CA mutation wasnot detected in ptDNA had a low percentage of mutantPIK3CA in the tumor sample (not detected by Sangersequencing) and a small amount of total plasma DNA("5 ng). Importantly, none of the patients with PIK3CAwild-type tumors had detectable PIK3CA mutations inpresurgery plasma DNA. These data demonstrate a sensi-tivity of 93.3% (95% CI, 75.5%–93.3%), specificity of100% (95% CI, 82.2%–100.0%), and accuracy of 96.7%(95% CI, 78.9%–96.7%) of ddPCR for detecting mutantPIK3CA in presurgery ptDNA.

Table 1. Patient characteristics

PatientAge at diagnosis(media, n ¼ 60) Stage TNM Histology ER PR HER2

1 66 IA T1c N0(iþ) Mx Lobular Positive Positive Negative2 63 IIA T1b N1 Mx Ductal Positive Positive Negative3 52 IA T1c N0 Mx Ductal/lobular Positive Positive Negative4 77 IA T1b N0 Mx Lobular Positive Positive Negative5 48 IA T1c N0 Mx Ductal Negative Negative Negative6 38 IIB T2 N1 Mx Ductal Positive Positive Negative7 49 IIA T2 N0 Mx Ductal Positive Positive Negative8 51 IA T1c N0 M0 Ductal Positive Positive Negative9 48 IIA T2 N0 Mx Ductal Positive Positive Negative10 55 IA T1c N0 M0 Ductal Positive Positive Negative11 71 IA T1c N0 Mx Ductal Positive Negative Negative12 69 IIA T2 N0(i-) Mx Lobular Positive Positive Negative13 52 IA T1c N0 Mx Ductal/lobular Positive Positive Negative14 64 IIA R: T1a N1 Mx Ductal Positive Positive Negative

IIIA L: T1b N2 Mx Lobular Positive Positive Negative15 75 IA T1b N0 Mx Lobular Positive Positive Negative16 51 IIB T2 N1 MX Metaplastic Negative Negative Negative17 67 IA T1c N0 Mx Ductal/lobular Positive Positive Negative18 63 IA T1c N0 Mx Ductal Positive Positive Negative19 60 IIA T1c N1 Mx Ductal Positive Positive Negative20 38 IIB T2 N1 Mx Ductal Positive Positive Negative21 72 IIA T2 N0 Mx Ductal Positive Positive Negative22 59 IA T1c N0 M0 Ductal Positive Positive Negative23 53 IIIA T2 N2 Mx Ductal Positive Positive Negative24 67 IA T1c N0 Mx Ductal/lobular Positive Positive Negative25 54 IA T1c N0 Mx Ductal Positive Positive Negative26 58 IIB T2 N1 MX Ductal Positive Positive Negative27 63 IIA T1 N1 Mx Ductal Positive Positive Negative28 55 IIA T1c N1 Mx Ductal Positive Positive Negative29 61 IIB T2 N1mi Mx Ductal Positive Positive Equivocala

NOTE: n ¼ 29. TNM, tumor–node–metastasis.aEquivocal by immunohistochemical staining 2þ, and FISH ratio of HER2:chromosome 17 ¼ 2.1.

Beaver et al.

Clin Cancer Res; 20(10) May 15, 2014 Clinical Cancer Research2646












Beaver et al.













Beaver et al.




In total, from the 15 PIK3CA mutations identified inprimary tumors by ddPCR, 14 PIK3CA mutations weredetected in 13of the presurgery plasma samples, as 1patient(patient 4) had concurrent E545K and H1047R mutationsidentified in both tumor and ptDNA. Of these PIK3CA-positive ptDNA samples, 8 patients, including patient 4,had stage IA disease with mutant PIK3CA ptDNA fractionalabundance ranging from 0.01% to 0.12%. Three patientswith stage IIA disease had plasma PIK3CA mutation levelswith a fractional abundance of 0.02%and0.01%,whereas 2stage IIB patients’ plasma samples demonstrated mutantPIK3CA at 0.01% and 2.99% fractional abundance. Frac-tional abundance for all ddPCR results are shown in Tables2 and 3 with 95% CIs in Supplementary Table S4. Repre-sentative ddPCR presurgery plasma DNA analyses areshown in Supplementary Fig. S1.

PIK3CA mutations detected in ptDNA by ddPCR aftersurgery

We then sought to determine whether any patients con-tinued to have detectable mutant PIK3CA after breast sur-gery. Postsurgical plasma specimens were collected from 17of the 29 patients, including 9 patients with a positivemutant PIK3CA presurgical ptDNA sample, and a 10thpatient (patient 4) whose tumor and presurgical ptDNAharbored both E545K andH1047R PIK3CAmutations for atotal of 10 potentially informative samples with 11 muta-tions identified in presurgery ptDNA. We collected post-surgery blood samples within 14 days after surgery in 5 ofthese patients as initially planned, whereas logistical issuesallowed us to collect the remaining 5 patients’ postsurgeryblood at times ranging from15 to 72 days after surgery. Twopatients, patients 16 and 22, had their blood collectedwhile

Table 2. Analysis of PIK3CA mutations in tumors and blood

PatientSequencing FFPEtumor tissue

ddPCR FFPEtumor tissue

ddPCR presurgeryplasma

1 Wild type H1047R (9.4%) H1047R (0.03%)2 Wild type Wild type Wild type3 Wild type Wild type Wild type4 Wild type E545K (28.9%) E545K (0.01%)

H1047R (6%) H1047R (0.02%)5 H1047R H1047R (25.5%) H1047R (0.02%)6 Wild type Wild type Wild type7 Wild type Wild type Wild type8 H1047R H1047R (26%) H1047R (0.12%)9 E545K E545K (43.7%) E545K (0.02%)10 Wild type Wild type Wild type11 H1047R H1047R (13.8%) H1047R (0.01%)12 Wild type Wild type Wild type13 Wild type E545K (16.1%) Wild type14 R:Wild type Wild type Wild type

L:Wild type Wild type Wild type15 Wild type Wild type Wild type16 H1047R H1047R (32.2%) H1047R (2.99%)17 E545K E545K (55.6%) E545K (0.07%)18 Wild type Wild type Wild type19 E545K E545K (20.3%) E545K (0.01%)20 Wild type Wild type Wild type21 Wild type Wild type Wild type22 H1047R H1047R (28.9%) H1047R (0.02%)23 Wild type Wild type Wild type24 Wild type Wild type Wild type25 H1047R H1047R (30.5%) H1047R (0.01%)26 Wild type Wild type Wild type27 Wild type Wild type Wild type28 Wild type H1047R (9.5%) H1047R (0.02%)29 H1047R H1047R (43.1%) H1047R (0.01%)

NOTE: Tumor and blood samples from 29 patients with early-stage breast cancer were analyzed for PIK3CAmutations using Sangersequencing FFPE tumor tissue, ddPCR of FFPE tumors (ddPCR FFPE tumor tissue) and presurgery plasma DNA (ddPCR presurgeryplasma). Percentage reflects fractional abundance of mutant PIK3CA (E545K or H1047R) to total PIK3CA DNA.

Detecting Plasma Tumor DNA in Early-Stage Breast Cancer

www.aacrjournals.org Clin Cancer Res; 20(10) May 15, 2014 2647



Beaver, J. A. et al. Detection of cancer DNA in plasma of patients with early-stage breast cancer. Clinical Cancer Research 20, 2643–2650 (2014). IF=8.2identified 2 additional PIK3CAH1047R mutations, 1 addi-

tional PIK3CA E545K mutation and 1 sample with bothH1047R and E545K mutations. The prevalence of PIK3CAmutations detected per tumor by ddPCR was 46.7% (14 of30). Results comparing the FFPE and ddPCR analyses withfractional abundance are shown in Table 2.









Beaver et al.













Beaver et al.




Sensitive method (ddPCR) 0.01%規格檢驗Primary腫瘤

Insensitive method (Sequencing) 10%規格檢驗Primary腫瘤

Sensitive method (ddPCR) 0.01%規格檢驗⼿手術前⾎血液

以靈敏⽅方式檢驗腫瘤

State of the Art0.1%濃度










Beaver et al.




正確率13/1492.8%

正確率10/1471.4%

988 VOLUME 14 | NUMBER 9 | SEPTEMBER 2008 NATURE MEDICINE

dance dropped precipitously thereafter. The ctDNA abundance then climbed back to higher levels over the next several months (Fig. 4).

Eleven of the subjects in our cohort received chemotherapy dur-ing the course of the study. In three of these subjects, ctDNA levels declined during the treatment (Fig. 4 and Supplementary Fig. 4). An example is provided by subject 8: ctDNA decreased by more than 99.9%, whereas tumor volume (composed of live and dead neoplastic cells in addition to stromal cells) decreased only slightly (Fig. 4). In six subjects, there was an immediate rise in ctDNA after discontinuation of chemotherapy, as is evident in subjects 8 and 11 after the first chemotherapy (Fig. 4) and in subjects 1, 4, 10 and 12 (Supplementary Fig. 4).

Comparison with carcinoembryonic antigenCarcinoembryonic antigen (CEA) is the standard biomarker for fol-lowing disease in subjects with colorectal cancer and is routinely used in the management of the disease10. Only ten of the eighteen sub-jects had CEA levels >5 ng ml–1 (the boundary of the normal range) before study entry (Table 1). This difference in sensitivity between the two assays (ctDNA versus CEA) was statistically significant; 56% versus 100%, respectively (P = 0.008, McNemar test). Moreover, even in those subjects with positive CEA levels before surgery, complete tumor resection resulted in a much less marked decrease in CEA than that observed with ctDNA (median decrease of 99.0% versus 32.5% in ctDNA versus CEA, respectively; P < 0.001, Student’s t-test). There was a modest overall correlation between CEA abundance and ctDNA levels after correcting for clustering within subjects (R2 = 0.20, P < 0.001, Supplementary Fig. 1b). Finally, when measured at the first post-operative follow-up visit on days 24–48, the ability of CEA levels to predict recurrent disease was less impressive than that of ctDNA levels (P = 0.03 by Mantel-Cox log-rank test, Fig. 3b).

DISCUSSIONThe results reported herein show that ctDNA is a promising biomarker for following the course of therapy in patients with metastatic colorectal cancer. ctDNA was detectable in all subjects before surgery, and serial blood sampling revealed oscillations in the level of ctDNA that corre-lated with the extent of surgical resection. Subjects who had detectable ctDNA after surgery generally relapsed within 1 year. The ctDNA seemed to be a much more reliable and sensitive indicator than the current standard biomarker (CEA) in this cohort of subjects.

Our studies are consistent with others that have shown that ctDNA can be detected in subjects with cancer, particularly in advanced tumors6. However, most such previous studies have not used techniques suffi-ciently sensitive to detect the low levels of ctDNA found in many of the subjects evaluated in the current study. Moreover, one of the crucial and distinguishing features of our approach lies in the ability to precisely measure the level of ctDNA rather than to simply determine whether or not ctDNA is detectable.

The results of our study suggest that ctDNA levels reflect the total systemic tumor burden, in that ctDNA levels decreased upon complete surgery and generally increased as new lesions became apparent upon radiological examination. However, whether ctDNA levels are exactly proportional to systemic tumor burden cannot be definitively deter-mined, because there is no independent way to measure systemic total burden at this time. Radiographs are inaccurate, because lesions that are observed upon imaging are composed of live neoplastic cells, dead neo-plastic cells and varying amounts of non-neoplastic cells (stromal fibro-blasts, inflammatory cells, vasculature, and the like)11. The proportion of these cell types in any lesion is unknown. Additionally, micrometastatic lesions that are smaller than a few millimeters, which in aggregate may

injury is consistent with the observation that the total amount of DNA in the plasma (mutant plus normal) increased immediately after surgery in all subjects (Supplementary Fig. 3 online).

Though the amount of ctDNA generally decreased after surgery, it did not decrease to undetectable levels in most cases. Plasma samples were available from the first follow-up visit, 13–56 d after surgery, in 20 instances. ctDNA was still detectable in 16 of these 20 instances, and recurrences occurred in all but one of these 16 (Table 1). In a marked contrast, no recurrence occurred in the four subjects in whom ctDNA was undetectable at the first follow-up visit (Table 1). The difference in recurrence rate between subjects with and without detectable ctDNA at the first follow-up was significant (P = 0.006 by Mantel-Cox log-rank test, Fig. 3a).

Representative time courses of ctDNA along with clinical and radiologic data on two subjects are provided in Figure 4, and simi-lar data on all other subjects are shown in Supplementary Figure 4 online. Subjects 8 and 11 had more than one surgical procedure during the study, providing special opportunities to assess changes in ctDNA after repeated, controlled manipulation of tumor bur-den. Both of these subjects had incomplete resections in their initial surgery, and their ctDNA levels did not decrease (Fig. 4). They had complete resections in their second surgery, and the ctDNA abun-

Undetectable ctDNA

Detectable ctDNA

Undetectable CEA

Detectable CEA

Rec

urre

nce-

free

sur

viva

l (%

)R

ecur

renc

e-fr

ee s

urvi

val (

%)

Time (d)

Time (d)

100

80

60

40

20

0

100

80

60

40

20

0

0 200 400 600 800

0 200 400 600 800

Figure 3 Recurrence-free survival, as detected by ctDNA and CEA. (a) The difference in recurrence-free survival in subjects with detectable versus undetectable post-operative ctDNA levels (P = 0.006 by Mantel-Cox log-rank test). (b) The difference in recurrence-free survival in subjects with detectable versus undetectable post-operative CEA levels (P = 0.03 by Mantel-Cox log-rank test).

a

b

T E C H N I C A L R E P O R T S

©20

08 N

atur

e Pu

blis

hing

Gro

up h

ttp://

ww

w.n

atur

e.co

m/n

atur

emed

icin

e

Diehl F, Schmidt K, Choti MA, et al. Circulating mutant DNA to assess tumor dynamics. Nat Med 2008;14(9):985–90.Circulating tumour DNA and CT monitoring in patients with untreated diffuse large B-cell lymphoma: a correlative biomarker study. Lancet Oncol. 16, 541–549 (2015). Montagut, C., Siravegna, G. & Bardelli, A. Liquid biopsies to evaluate early therapeutic response in colorectal cancer. Ann. Oncol. 26, 1525–1527 (2015).

by the classical RECIST criteria (Figure 1) . Tie et al. report a cor-relation between changes in ctDNA mutation levels after one cycleof chemotherapy and response by RECIST criteria 8–12 weeksafter the onset of therapy, and more importantly a trend toward acorrelation between changes in ctDNA and progression-free sur-vival. Interestingly, although very early changes (d+3) in ctDNAdid not correlate with response, a spike in ctDNAwas observed inthree patients with a striking response, suggesting that earlychanges in plasma mutational loads may reflect DNA release intothe bloodstream and may be used to identify the best responders.A test that anticipates response to a given drug early during the

course of treatment without waiting for image changes in the CTscan weeks after the onset of therapy, potentially allows for anearly switch in treatment, avoiding unnecessary side-effects, en-hancing efficacy and minimizing costs. Moreover, recent evidenceshows that early tumor shrinkage in the treatment of metastaticcolorectal cancer correlates with longer survival.What are the implications of this work? The encouraging

results in this paper support the use of ctDNA as an early in-dicator of tumor response in metastatic colorectal cancerpatients. However, given the small size of the cohort, thesedata should be viewed as hypothesis-generating and must bereplicated in the context of large clinical trials to show a clinic-ally and statistically significant impact on survival of patients.From a methodological standpoint, the approach is relativelyeasy to translate in daily clinical practice. The approachrequires availability of tumor tissue (surgery or biopsy) toidentify patient-specific mutations. While this is rarely a

limitation for colorectal cancer patients, in other tumor typessuch as lung tumors, access to lesions is more difficult and maysometimes be a limitation.The idea of assessing response to treatment in cancer patients

using mutation levels is reminiscent of the use of viral load tomonitor therapy response in HIV patients. Will ctDNA substi-tute RECIST criteria in the near future? A number of reasonssuggest that imaging will always be necessary to evaluate the siteof metastatic disease, the resectability of tumor lesions or theclinical compromise of adjacent anatomic structures. Therefore,ctDNA and RECIST assessment will likely complement eachother, and together with other methods (i.e. functional imaging)will define new integrated standards for evaluation of therapyin oncology. As emphasized by this study, the opportunitiesoffered by circulating free tumor DNA are only starting to beexplored but it is already clear that liquid biopsies are here tostay and will become a central asset in the management ofcancer patients.

C. Montagut1,2, G. Siravegna3,4,5 & A. Bardelli3,4*1Department of Medical Oncology;

2Cancer Research Program, FIMIM, Hospital del Mar,Barcelona, Spain;

3Department of Oncology, University of Torino, Candiolo;4Candiolo Cancer Institute – FPO, IRCCS, Candiolo;

5FIRC Institute of Molecular Oncology (IFOM), Milan, Italy(*E-mail: [email protected])

0

100

200

300

CE

A (

ng/m

l)

400

500

600

700

800

900 1 2 3 4 5 6 7 60

50

40

30

Mut

ated

alle

les

(%)

20Response byRECIST (CT scan)

Molecularresponse byliquid biopsy

Blood draws (ctDNA)

CEA

Treatment cycles

ctDNA mutation in plasma

Tumor burden

10

0

Figure 1. Liquid biopsies to monitor early therapeutic response in a representative CRC patient. Dark grey line (blue online) and black dotted line (greenonline) indicate mutations in ctDNA and CEA likely levels, respectively, at different time points. Light grey area (pink online) represents tumor load (cm). Thedark grey (red online) and the light grey (green online) helices represent mutated and wild-type plasma DNA fragments, respectively. Molecular assessment ofresponse by liquid biopsy anticipates clinical response by RECIST (cycle 6), as emphasized by the drop of the mutant alleles before cycle 2.

| Montagut et al. Volume 26 | No. 8 | August 2015

editorials Annals of Oncology

at National Taiw

an Univ. H

ospital on August 9, 2015

http://annonc.oxfordjournals.org/D

ownloaded from

Cancer type Taiwan new cases

EGFR mutation molecular prevalence

Estimated EGFR mutation cases

EGFR mutation contribution

Lung (adenocarinoma/adenosequmaous) 2,982 61.00% 1,819 75.1%

Lung (small cell) 111 6.00% 7 0.3%

Lung (squamous cell) 228 6.00% 14 0.6%

Lung (large cell) 15 5.00% 1 0.0%

Lung (others)* 375 28.00% 105 4.3%

Lung (all) 3,711 n/a 1,945 80.3%Esophagus 150 2.10% 3 0.1%

Thyroid 1,846 1.02% 19 0.8%

Colon 5,337 2.28% 122 5.0%Bile 437 2.11% 9 0.4%

Pancreatic 686 0.35% 2 0.1%

Stomach 1,444 3.92% 57 2.3%

Liver 3,333 0.76% 25 1.0%

Leukemia 759 0.97% 7 0.3%

Lymphoma 1,045 0.97% 10 0.4%

Bladder 584 1.42% 8 0.3%

CNS 226 6.00% 14 0.6%

Breast 8,926 1.13% 101 4.2%Uteri/Endometrium 1,496 3.83% 57 2.4%Ovary 1,113 2.02% 22 0.9%

Cervix 1,796 1.11% 20 0.8%

Lung cancer and prognosis in taiwan: a population-based cancer registry. J Thorac Oncol. 2013 Sep;8(9):1128-35. doi: 10.1097/JTO.0b013e31829ceba4.台灣癌症申報發⽣生⼈人數按組織病理、性別及年齡分類Cosmic » Cancer Browser » LungA prospective, molecular epidemiology study of EGFR mutations in Asian patients withadvanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol. 2014 Feb;9(2):154-62.

Female EGFR mutation

Lung (all)80%

Cancer type Taiwan new cases

EGFR mutation molecular prevalence

Estimated EGFR mutation cases

EGFR mutation contribution

Lung (adenocarinoma/adenosequmaous) 2,961 44% 1,303 57.9%

Lung (small cell) 859 6% 52 2.3%

Lung (squamous cell) 1,622 6% 97 4.3%

Lung (large cell) 40 5% 2 0.1%

Lung (others)* 840 28% 235 10.5%

Lung (all) 6,322 n/a 1,689 75.1%Esophagus 1,898 2.10% 40 1.8%

Thyroid 568 1.02% 6 0.3%

Colon 7,151 2.28% 163 7.2%Bile 493 2.11% 10 0.5%

Pancreatic 962 0.35% 3 0.1%

Stomach 2,404 3.92% 94 4.2%Liver 7,747 0.76% 59 2.6%

Leukemia 1,093 0.97% 11 0.5%

Lymphoma 1,295 0.97% 13 0.6%

Bladder 1,419 1.42% 20 0.9%

CNS 351 6% 21 0.9%

Prostate 4,013 3% 120 5.4%

Lung cancer and prognosis in taiwan: a population-based cancer registry. J Thorac Oncol. 2013 Sep;8(9):1128-35. doi: 10.1097/JTO.0b013e31829ceba4.台灣癌症申報發⽣生⼈人數按組織病理、性別及年齡分類Cosmic » Cancer Browser » LungA prospective, molecular epidemiology study of EGFR mutations in Asian patients withadvanced non-small-cell lung cancer of adenocarcinoma histology (PIONEER). J Thorac Oncol. 2014 Feb;9(2):154-62.

Male EGFR mutation

Lung (all)75%

NGS

ddPCR

BEAMing

CloDiA PCR

2002

2006

2009

2012

cf DNA 檢驗⽅方式價格偵測突變

$ 70,000

$ 50,000

$ 120,000

$?,???

NGS

ddPCR

BEAMing

CloDiA PCR

2002

2006

2009

2012

cf DNA 檢驗⽅方式價格偵測突變

$ 2,500

$ 1,500

$ 4,000

$???


TEST 1 2 3 4 5 6 7 8 9 10

EGFR Del19

EGFR Exon 20 T790M

EGFR Exon 21 L858R

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion


TEST 1 2 3 4 5 6 7 8 9 10

EGFR Del19

EGFR Exon 20 T790M

EGFR Exon 21 L858R

Metabolicactivation


Normalcell

CARCINOGEN

MALIGNANT NEOPLASM

PRENEOPLASTIC CLONE





Detoxification

Detoxification

INIT

IATI

ON

DNArepair

Celldeath

PRO

MO

TIO

N

Excretion

Health & Medicine

空氣汙染引起 EGFR基因突變肺癌