Chloe C. Su

All Publications

• Eligibility and Prognostic Performance of Smoking Duration-Based Versus Pack-Year-Based U.S. National Lung Cancer Screening Criteria Across Racial and Ethnic Groups. Annals of internal medicine Su, C. C., Ding, V. Y., Ten Haaf, K., Wu, J. T., Freedman, N. D., Backhus, L. M., Leung, A. N., Lui, N. S., Haiman, C. A., Park, S. L., Neal, J. W., Meza, R., Tammemägi, M. C., Cheng, I., Le Marchand, L., Wakelee, H. A., Choi, E., Han, S. S. 2025

  Abstract

  The U.S. Preventive Services Task Force expanded lung cancer (LC) screening eligibility in 2021 (USPSTF-2021) by decreasing the minimum number of smoking pack-years from 30 to 20. Underrepresented minorities still experience disparities in screening eligibility.To evaluate screening eligibility and prognostic performance of alternative smoking duration-based criteria versus USPSTF-2021 (primary outcome) and risk-based screening using the recalibrated Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 (PLCOm2012update) model (secondary outcome) across diverse racial and ethnic groups.Prospective, population-based Multiethnic Cohort linked to SEER (Surveillance, Epidemiology, and End Results) registries.California and Hawai'i, with recruitment from 1993 to 1996.105 261 adults aged 45 to 75 years with a history of smoking.Hypothetical eligibility and prognostic performance (sensitivity and specificity) in detecting 6-year LC.Under USPSTF-2021, 24.0% of the cohort would be eligible for screening; a 30-year smoking duration yielded the closest eligibility rate (27.5%). Compared with USPSTF-2021, the 30-year duration criteria would reduce eligibility gaps across all races relative to Whites, most notably in African Americans (30.4% vs. 28.8% for Whites under duration-based; 21.4% vs. 30.2% for Whites under USPSTF-2021) and Latinos (25.1% vs. 28.8% for Whites under duration-based; 15.7% vs. 30.2% for Whites under USPSTF-2021). Prognostic sensitivity to identify LC within 6 years increased across all races under the 30-year duration criteria, although specificity decreased commensurately. At matched overall eligibility (27.5%), a risk-based PLCOm2012update 6-year threshold of 1.1% improved both sensitivity and specificity in the overall cohort. However, it widened the eligibility gap between Latinos and Whites (14.4% vs. 31.3%) and demonstrated lower sensitivity in Latinos than duration-based criteria (59.7% vs. 69.8%).Cohort geography and enrollment period may limit generalizability. Overdiagnosis was not measured.Compared with USPSTF-2021, the 30-year duration-based criteria could reduce the eligibility gaps among African Americans and Latinos relative to Whites while improving 6-year LC detection sensitivity across all races.National Institutes of Health.

  View details for DOI 10.7326/ANNALS-25-00464

  View details for PubMedID 41397256

• Leveraging large language models to extract smoking history from clinical notes for lung cancer surveillance. NPJ digital medicine Luo, I., Graber-Naidich, A., Zhang, M., Kaushik, R., Nieda, G. M., Chen, T., Gu, B., Choi, E., Ding, V. Y., Gunturkun, F., Satoyoshi, M., Bhat, A., Lee, T. Y., Su, C. C., Ellis-Caleo, T. J., Henry, A. S., Desai, M., Backhus, L. M., Lui, N. S., Leung, A., Neal, J. W., Kurian, A. W., Langlotz, C. P., Wakelee, H. A., Liang, S. Y., Khan, A., Han, S. S. 2025; 8 (1): 731

  Abstract

  Accurate smoking documentation in electronic health records (EHRs) is crucial for risk assessment and patient monitoring. However, key information is often missing or inaccurately recorded. Large language models (LLMs) present a promising solution for interpreting clinical narratives to extract comprehensive smoking data. We developed a framework utilizing LLMs combined with rule-based longitudinal smoothing techniques to enhance data quality. We compared generative LLMs (Gemini-1.5-Flash, PaLM-2-Text-Bison, GPT-4) against BERT-based models using 1683 manually annotated clinical notes from 518 patients across Stanford and Sutter Health systems. Generative LLMs achieved superior performance ( > 96% accuracy) across seven smoking variables, with external validation showing robust generalizability (97.5-98.8% accuracy). We deployed Gemini-1.5-Flash to 79,408 notes from 4792 lung cancer patients, demonstrating that risk model-based surveillance incorporating smoking factors outperformed NCCN Guidelines in identifying second malignancies. Our study highlights the potential of generative LLMs to improve smoking history documentation quality, enhancing lung cancer surveillance and broader clinical applications.

  View details for DOI 10.1038/s41746-025-02009-y

  View details for PubMedID 41315854

  View details for PubMedCentralID 11745215

• Automatic Abstraction of Computed Tomography Imaging Indication Using Natural Language Processing for Evaluation of Surveillance Patterns in Long-Term Lung Cancer Survivors. JCO clinical cancer informatics Khan, A., Choi, E., Su, C., Graber-Naidich, A., Henry, S., Satoyoshi, M. L., Bhat, A., Kurian, A. W., Liang, S. Y., Neal, J., Gould, M., Leung, A., Wakelee, H. A., Backhus, L. M., Langlotz, C., Wu, J., Han, S. S. 2025; 9: e2400279

  Abstract

  Despite its routine use to monitor patients with lung cancer (LC), real-world evaluations of the impact of computed tomography (CT) surveillance on overall survival (OS) have been inconsistent. A major confounder is the absence of imaging indications because patients undergo CT scans for purposes beyond surveillance, like symptom evaluations (eg, cough) linked to poor survival. We propose a novel natural language processing model to predict CT imaging indications (surveillance v others).We used electronic health records of 585 long-term LC survivors (≥5 years) at Stanford, followed for up to 22 years. Their 3,362 post-5-year CT reports (including 1,672 manually annotated) were used for modeling by integrating structured variables (eg, CT intervals) with key-phrase analysis of radiology reports. Naïve analysis compared OS in patients with CT for any indications (including symptoms) versus those without post-5-year CT, as in previous studies. Using model-predicted indications, we conducted exploratory analyses to compare OS between those with post-5-year surveillance CT and those without.The model showed high discrimination (AUC, 0.86), with key predictors including a longer interval (≥6-month) from the previous CT (odds ratios [OR], 5.50; P < .001) and surveillance-related key phrases (OR, 1.37; P = .03). Propensity-adjusted survival analysis indicated better OS for patients with any post-5-year surveillance CT versus those without (adjusted hazard ratio, 0.60; P = .016). By contrast, no significant survival difference was found (P = .53) between patients with any CT versus those without post-5-year CT.Our model abstracted CT indications from real-world data with high discrimination. Exploratory analyses revealed the obscured imaging-OS association when considering indications, highlighting the model's potential for future real-world studies.

  View details for DOI 10.1200/CCI-24-00279

  View details for PubMedID 40700679

• Enabling national identification of lung cancer screening eligibility with large language models. Wu, J., Conover, S., Su, C., Corrigan, J., Culnan, J., Liu, Y., Kelley, M. J., Do, N., Arya, S., Harris, A. H. S., Langlotz, C., Wiener, R., Branch-Elliman, W., Han, S., Fillmore, N. LIPPINCOTT WILLIAMS & WILKINS. 2025: e13613

  View details for DOI 10.1200/JCO.2025.43.16_suppl.e13613

  View details for Web of Science ID 001509490400001

• Correction: The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer. Cancer immunology, immunotherapy : CII Wu, J. T., Corrigan, J., Su, C., Dumontier, C., La, J., Khan, A., Arya, S., Harris, A. H., Backhus, L., Das, M., Do, N. V., Brophy, M. T., Han, S. S., Kelley, M., Fillmore, N. R. 2024; 74 (1): 34

  View details for DOI 10.1007/s00262-024-03875-3

  View details for PubMedID 39739108

• Racial and Ethnic Differences in Second Primary Lung Cancer Risk among Lung Cancer Survivors. JNCI cancer spectrum Choi, E., Hua, Y., Su, C. C., Wu, J. T., Neal, J. W., Leung, A. N., Backhus, L. M., Haiman, C., Le Marchand, L., Liang, S., Wakelee, H. A., Cheng, I., Han, S. S. 2024

  Abstract

  BACKGROUND: Recent therapeutic advances have improved survival among lung cancer (LC) patients, who are now at high risk of second primary lung cancer (SPLC). Hispanics comprise the largest minority in the U.S., who have shown a lower LC incidence and mortality than other races, yet their SPLC risk is poorly understood.We quantified the SPLC incidence patterns among Hispanics vs other races.METHODS: We used data from the Multiethnic Cohort, a population-based cohort of five races (African American, Japanese American, Hispanic, Native Hawaiian, and White), recruited between 1993-1996 and followed through 2017. We identified patients diagnosed with initial primary lung cancer (IPLC) and SPLC via linkage to SEER registries. We estimated the 10-year cumulative incidence of IPLC (in the entire cohort) and SPLC (among IPLC patients). A standardized incidence ratio (SIR) was calculated as the ratio of SPLC-to-IPLC incidence by race/ethnicity.RESULTS: Among 202,692 participants, 6,788 (3.3%) developed IPLC over 3,871,417 person-years. The 10-year cumulative IPLC incidence was lower among Hispanics (0.80%, [0.72-0.88]) vs Whites (1.67%, [1.56-1.78]) or Blacks (2.44%, [2.28-2.60]). However, the 10-year SPLC incidence following IPLC was higher among Hispanics (3.11%, [1.62-4.61]) vs Whites (2.80%, [1.94-3.66]) or Blacks (2.29%, [1.48-3.10]), resulting in a significantly higher SIR for Hispanics (SIR=8.27, [5.05-12.78]) vs Whites (SIR=5.60, [4.11-7.45]) or Blacks (SIR=3.48, [2.42-4.84])(p<.001).CONCLUSION: Hispanics have a higher SPLC incidence following IPLC than other races, which may be potentially due to better survival after IPLC and extended duration for SPLC development. Continuing surveillance is warranted to reduce racial disparities among LC survivors.

  View details for DOI 10.1093/jncics/pkae072

  View details for PubMedID 39186009

• The performance status gap in immunotherapy for frail patients with advanced non-small cell lung cancer. Cancer immunology, immunotherapy : CII Wu, J. T., Corrigan, J., Su, C., Dumontier, C., La, J., Khan, A., Arya, S., Harris, A. H., Backhus, L., Das, M., Do, N. V., Brophy, M. T., Han, S. S., Kelley, M., Fillmore, N. R. 2024; 73 (9): 172

  Abstract

  In advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitor (ICI) monotherapy is often preferred over intensive ICI treatment for frail patients and those with poor performance status (PS). Among those with poor PS, the additional effect of frailty on treatment selection and mortality is unknown.Patients in the veterans affairs national precision oncology program from 1/2019-12/2021 who received first-line ICI for advanced NSCLC were followed until death or study end 6/2022. Association of an electronic frailty index with treatment selection was examined using logistic regression stratified by PS. We also examined overall survival (OS) on intensive treatment using Cox regression stratified by PS. Intensive treatment was defined as concurrent use of platinum-doublet chemotherapy and/or dual checkpoint blockade and non-intensive as ICI monotherapy.Of 1547 patients receiving any ICI, 66.2% were frail, 33.8% had poor PS (≥ 2), and 25.8% were both. Frail patients received less intensive treatment than non-frail patients in both PS subgroups (Good PS: odds ratio [OR] 0.67, 95% confidence interval [CI] 0.51 - 0.88; Poor PS: OR 0.69, 95% CI 0.44 - 1.10). Among 731 patients receiving intensive treatment, frailty was associated with lower OS for those with good PS (hazard ratio [HR] 1.53, 95% CI 1.2 - 1.96), but no association was observed with poor PS (HR 1.03, 95% CI 0.67 - 1.58).Frail patients with both good and poor PS received less intensive treatment. However, frailty has a limited effect on survival among those with poor PS. These findings suggest that PS, not frailty, drives survival on intensive treatment.

  View details for DOI 10.1007/s00262-024-03763-w

  View details for PubMedID 38954019

  View details for PubMedCentralID 9359868

• Wnt signaling couples G2 phase control with differentiation during hematopoiesis in Drosophila. Developmental cell Goins, L. M., Girard, J. R., Mondal, B. C., Buran, S., Su, C. C., Tang, R., Biswas, T., Kissi, J. A., Banerjee, U. 2024

  Abstract

  During homeostasis, a critical balance is maintained between myeloid-like progenitors and their differentiated progeny, which function to mitigate stress and innate immune challenges. The molecular mechanisms that help achieve this balance are not fully understood. Using genetic dissection in Drosophila, we show that a Wnt6/EGFR-signaling network simultaneously controls progenitor growth, proliferation, and differentiation. Unlike G1-quiescence of stem cells, hematopoietic progenitors are blocked in G2 phase by a β-catenin-independent (Wnt/STOP) Wnt6 pathway that restricts Cdc25 nuclear entry and promotes cell growth. Canonical β-catenin-dependent Wnt6 signaling is spatially confined to mature progenitors through localized activation of the tyrosine kinases EGFR and Abelson kinase (Abl), which promote nuclear entry of β-catenin and facilitate exit from G2. This strategy combines transcription-dependent and -independent forms of both Wnt6 and EGFR pathways to create a direct link between cell-cycle control and differentiation. This unique combinatorial strategy employing conserved components may underlie homeostatic balance and stress response in mammalian hematopoiesis.

  View details for DOI 10.1016/j.devcel.2024.05.023

  View details for PubMedID 38866012

• Second Primary Lung Cancer Among Lung Cancer Survivors Who Never Smoked. JAMA network open Choi, E., Su, C. C., Wu, J. T., Aredo, J. V., Neal, J. W., Leung, A. N., Backhus, L. M., Lui, N. S., Le Marchand, L., Stram, D. O., Liang, S. Y., Cheng, I., Wakelee, H. A., Han, S. S. 2023; 6 (11): e2343278

  Abstract

  Lung cancer among never-smokers accounts for 25% of all lung cancers in the US; recent therapeutic advances have improved survival among patients with initial primary lung cancer (IPLC), who are now at high risk of developing second primary lung cancer (SPLC). As smoking rates continue to decline in the US, it is critical to examine more closely the epidemiology of lung cancer among patients who never smoked, including their risk for SPLC.To estimate and compare the cumulative SPLC incidence among lung cancer survivors who have never smoked vs those who have ever smoked.This population-based prospective cohort study used data from the Multiethnic Cohort Study (MEC), which enrolled participants between April 18, 1993, and December 31, 1996, with follow-up through July 1, 2017. Eligible individuals for this study were aged 45 to 75 years and had complete smoking data at baseline. These participants were followed up for IPLC and further SPLC development through the Surveillance, Epidemiology, and End Results registry. The data were analyzed from July 1, 2022, to January 31, 2023.Never-smoking vs ever-smoking exposure at MEC enrollment.The study had 2 primary outcomes: (1) 10-year cumulative incidence of IPLC in the entire study cohort and 10-year cumulative incidence of SPLC among patients with IPLC and (2) standardized incidence ratio (SIR) (calculated as the SPLC incidence divided by the IPLC incidence) by smoking history.Among 211 414 MEC participants, 7161 (3.96%) developed IPLC over 4 038 007 person-years, and 163 (2.28%) developed SPLC over 16 470 person-years. Of the participants with IPLC, the mean (SD) age at cohort enrollment was 63.6 (7.7) years, 4031 (56.3%) were male, and 3131 (43.7%) were female. The 10-year cumulative IPLC incidence was 2.40% (95% CI, 2.31%-2.49%) among ever-smokers, which was 7 times higher than never-smokers (0.34%; 95% CI, 0.30%-0.37%). However, the 10-year cumulative SPLC incidence following IPLC was as high among never-smokers (2.84%; 95% CI, 1.50%-4.18%) as ever-smokers (2.72%; 95% CI, 2.24%-3.20%), which led to a substantially higher SIR for never-smokers (14.50; 95% CI, 8.73-22.65) vs ever-smokers (3.50; 95% CI, 2.95-4.12).The findings indicate that SPLC risk among lung cancer survivors who never smoked is as high as among those with IPLC who ever-smoked, highlighting the need to identify risk factors for SPLC among patients who never smoked and to develop a targeted surveillance strategy.

  View details for DOI 10.1001/jamanetworkopen.2023.43278

  View details for PubMedID 37966839

• Overall Survival Among Patients With De Novo Stage IV Metastatic and Distant Metastatic Recurrent Non-Small Cell Lung Cancer. JAMA network open Su, C. C., Wu, J. T., Choi, E., Myall, N. J., Neal, J. W., Kurian, A. W., Stehr, H., Wood, D., Henry, S. M., Backhus, L. M., Leung, A. N., Wakelee, H. A., Han, S. S. 2023; 6 (9): e2335813

  Abstract

  Despite recent breakthroughs in therapy, advanced lung cancer still poses a therapeutic challenge. The survival profile of patients with metastatic lung cancer remains poorly understood by metastatic disease type (ie, de novo stage IV vs distant recurrence).To evaluate the association of metastatic disease type on overall survival (OS) among patients with non-small cell lung cancer (NSCLC) and to identify potential mechanisms underlying any survival difference.Cohort study of a national US population based at a tertiary referral center in the San Francisco Bay Area using participant data from the National Lung Screening Trial (NLST) who were enrolled between 2002 and 2004 and followed up for up to 7 years as the primary cohort and patient data from Stanford Healthcare (SHC) for diagnoses between 2009 and 2019 and followed up for up to 13 years as the validation cohort. Participants from NLST with de novo metastatic or distant recurrent NSCLC diagnoses were included. Data were analyzed from January 2021 to March 2023.De novo stage IV vs distant recurrent metastatic disease.OS after diagnosis of metastatic disease.The NLST and SHC cohort consisted of 660 and 180 participants, respectively (411 men [62.3%] vs 109 men [60.6%], 602 White participants [91.2%] vs 111 White participants [61.7%], and mean [SD] age of 66.8 [5.5] vs 71.4 [7.9] years at metastasis, respectively). Patients with distant recurrence showed significantly better OS than patients with de novo metastasis (adjusted hazard ratio [aHR], 0.72; 95% CI, 0.60-0.87; P < .001) in NLST, which was replicated in SHC (aHR, 0.64; 95% CI, 0.43-0.96; P = .03). In SHC, patients with de novo metastasis more frequently progressed to the bone (63 patients with de novo metastasis [52.5%] vs 19 patients with distant recurrence [31.7%]) or pleura (40 patients with de novo metastasis [33.3%] vs 8 patients with distant recurrence [13.3%]) than patients with distant recurrence and were primarily detected through symptoms (102 patients [85.0%]) as compared with posttreatment surveillance (47 patients [78.3%]) in the latter. The main finding remained consistent after further adjusting for metastasis sites and detection methods.In this cohort study, patients with distant recurrent NSCLC had significantly better OS than those with de novo disease, and the latter group was associated with characteristics that may affect overall survival. This finding can help inform future clinical trial designs to ensure a balance for baseline patient characteristics.

  View details for DOI 10.1001/jamanetworkopen.2023.35813

  View details for PubMedID 37751203

• A functional genomics screen identifying blood cell development genes in Drosophila by undergraduates participating in a course-based research experience. G3 (Bethesda, Md.) Evans, C. J., Olson, J. M., Mondal, B. C., Kandimalla, P., Abbasi, A., Abdusamad, M. M., Acosta, O., Ainsworth, J. A., Akram, H. M., Albert, R. B., Alegria-Leal, E., Alexander, K. Y., Ayala, A. C., Balashova, N. S., Barber, R. M., Bassi, H., Bennion, S. P., Beyder, M., Bhatt, K. V., Bhoot, C., Bradshaw, A. W., Brannigan, T. G., Cao, B., Cashell, Y. Y., Chai, T., Chan, A. W., Chan, C., Chang, I., Chang, J., Chang, M. T., Chang, P. W., Chang, S., Chari, N., Chassiakos, A. J., Chen, I. E., Chen, V. K., Chen, Z., Cheng, M. R., Chiang, M., Chiu, V., Choi, S., Chung, J. H., Contreras, L., Corona, E., Cruz, C. J., Cruz, R. L., Dang, J. M., Dasari, S. P., De La Fuente, J. R., Del Rio, O. M., Dennis, E. R., Dertsakyan, P. S., Dey, I., Distler, R. S., Dong, Z., Dorman, L. C., Douglass, M. A., Ehresman, A. B., Fu, I. H., Fua, A., Full, S. M., Ghaffari-Rafi, A., Ghani, A. A., Giap, B., Gill, S., Gill, Z. S., Gills, N. J., Godavarthi, S., Golnazarian, T., Goyal, R., Gray, R., Grunfeld, A. M., Gu, K. M., Gutierrez, N. C., Ha, A. N., Hamid, I., Hanson, A., Hao, C., He, C., He, M., Hedtke, J. P., Hernandez, Y. K., Hlaing, H., Hobby, F. A., Hoi, K., Hope, A. C., Hosseinian, S. M., Hsu, A., Hsueh, J., Hu, E., Hu, S. S., Huang, S., Huang, W., Huynh, M., Javier, C., Jeon, N. E., Ji, S., Johal, J., John, A., Johnson, L., Kadakia, S., Kakade, N., Kamel, S., Kaur, R., Khatra, J. S., Kho, J. A., Kim, C., Kim, E. J., Kim, H. J., Kim, H. W., Kim, J. H., Kim, S. A., Kim, W. K., Kit, B., La, C., Lai, J., Lam, V., Le, N. K., Lee, C. J., Lee, D., Lee, D. Y., Lee, J., Lee, J., Lee, J., Lee, J., Lee, S., Lee, T. C., Lee, V., Li, A. J., Li, J., Libro, A. M., Lien, I. C., Lim, M., Lin, J. M., Liu, C. Y., Liu, S. C., Louie, I., Lu, S. W., Luo, W. Y., Luu, T., Madrigal, J. T., Mai, Y., Miya, D. I., Mohammadi, M., Mohanta, S., Mokwena, T., Montoya, T., Mould, D. L., Murata, M. R., Muthaiya, J., Naicker, S., Neebe, M. R., Ngo, A., Ngo, D. Q., Ngo, J. A., Nguyen, A. T., Nguyen, H. C., Nguyen, R. H., Nguyen, T. T., Nguyen, V. T., Nishida, K., Oh, S., Omi, K. M., Onglatco, M. C., Almazan, G. O., Paguntalan, J., Panchal, M., Pang, S., Parikh, H. B., Patel, P. D., Patel, T. H., Petersen, J. E., Pham, S., Phan-Everson, T. M., Pokhriyal, M., Popovich, D. W., Quaal, A. T., Querubin, K., Resendiz, A., Riabkova, N., Rong, F., Salarkia, S., Sama, N., Sang, E., Sanville, D. A., Schoen, E. R., Shen, Z., Siangchin, K., Sibal, G., Sin, G., Sjarif, J., Smith, C. J., Soeboer, A. N., Sosa, C., Spitters, D., Stender, B., Su, C. C., Summapund, J., Sun, B. J., Sutanto, C., Tan, J. S., Tan, N. L., Tangmatitam, P., Trac, C. K., Tran, C., Tran, D., Tran, D., Tran, V., Truong, P. A., Tsai, B. L., Tsai, P., Tsui, C. K., Uriu, J. K., Venkatesh, S., Vo, M., Vo, N., Vo, P., Voros, T. C., Wan, Y., Wang, E., Wang, J., Wang, M. K., Wang, Y., Wei, S., Wilson, M. N., Wong, D., Wu, E., Xing, H., Xu, J. P., Yaftaly, S., Yan, K., Yang, E., Yang, R., Yao, T., Yeo, P., Yip, V., Yogi, P., Young, G. C., Yung, M. M., Zai, A., Zhang, C., Zhang, X. X., Zhao, Z., Zhou, R., Zhou, Z., Abutouk, M., Aguirre, B., Ao, C., Baranoff, A., Beniwal, A., Cai, Z., Chan, R., Chien, K. C., Chaudhary, U., Chin, P., Chowdhury, P., Dalie, J., Du, E. Y., Estrada, A., Feng, E., Ghaly, M., Graf, R., Hernandez, E., Herrera, K., Ho, V. W., Honeychurch, K., Hou, Y., Huang, J. M., Ishii, M., James, N., Jang, G., Jin, D., Juarez, J., Kesaf, A. E., Khalsa, S. K., Kim, H., Kovsky, J., Kuang, C. L., Kumar, S., Lam, G., Lee, C., Lee, G., Li, L., Lin, J., Liu, J., Ly, J., Ma, A., Markovic, H., Medina, C., Mungcal, J., Naranbaatar, B., Patel, K., Petersen, L., Phan, A., Phung, M., Priasti, N., Ruano, N., Salim, T., Schnell, K., Shah, P., Shen, J., Stutzman, N., Sukhina, A., Tian, R., Vega-Loza, A., Wang, J., Wang, J., Watanabe, R., Wei, B., Xie, L., Ye, J., Zhao, J., Zimmerman, J., Bracken, C., Capili, J., Char, A., Chen, M., Huang, P., Ji, S., Kim, E., Kim, K., Ko, J., Laput, S. L., Law, S., Lee, S. K., Lee, O., Lim, D., Lin, E., Marik, K., Mytych, J., O'Laughlin, A., Pak, J., Park, C., Ryu, R., Shinde, A., Sosa, M., Waite, N., Williams, M., Wong, R., Woo, J., Woo, J., Yepuri, V., Yim, D., Huynh, D., Wijiewarnasurya, D., Shapiro, C., Levis-Fitzgerald, M., Jaworski, L., Lopatto, D., Clark, I. E., Johnson, T., Banerjee, U. 2021; 11 (1)

  Abstract

  Undergraduate students participating in the UCLA Undergraduate Research Consortium for Functional Genomics (URCFG) have conducted a two-phased screen using RNA interference (RNAi) in combination with fluorescent reporter proteins to identify genes important for hematopoiesis in Drosophila. This screen disrupted the function of approximately 3500 genes and identified 137 candidate genes for which loss of function leads to observable changes in the hematopoietic development. Targeting RNAi to maturing, progenitor, and regulatory cell types identified key subsets that either limit or promote blood cell maturation. Bioinformatic analysis reveals gene enrichment in several previously uncharacterized areas, including RNA processing and export and vesicular trafficking. Lastly, the participation of students in this course-based undergraduate research experience (CURE) correlated with increased learning gains across several areas, as well as increased STEM retention, indicating that authentic, student-driven research in the form of a CURE represents an impactful and enriching pedagogical approach.

  View details for DOI 10.1093/g3journal/jkaa028

  View details for PubMedID 33561251

• The Survival Impact of Second Primary Lung Cancer in Patients with Lung Cancer. Journal of the National Cancer Institute Choi, E., Luo, S. J., Aredo, J. V., Backhus, L. M., Wilkens, L. R., Su, C. C., Neal, J. W., Le Marchand, L., Cheng, I., Wakelee, H. A., Han, S. S. 2021

  Abstract

  Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC), but little is known about the survival impact of SPLC diagnosis.We analyzed data from 138,969 patients in the Surveillance, Epidemiology, and End Results (SEER), who were surgically treated for initial primary lung cancer (IPLC) in 1988-2013. Each patient was followed from the date of IPLC diagnosis to SPLC diagnosis (for those with SPLC) and last vital status through 2016. We performed multivariable Cox regression to evaluate the association between overall survival and SPLC diagnosis as a time-varying predictor. To investigate potential effect modification, we tested interaction between SPLC and IPLC stage. Using data from the Multiethnic Cohort Study (MEC) (N = 1,540 IPLC patients with surgery), we evaluated the survival impact of SPLC by smoking status. All statistical tests were 2-sided.A total of 12,115 (8.7%) patients developed SPLC in SEER over 700,421 person-years of follow up. Compared to patients with single primary lung cancer, those with SPLC had statistically significantly reduced overall survival (hazard ratio [HR]=2.12, 95% confidence interval [CI] = 2.06-2.17; P < .001). The effect of SPLC on reduced survival was more pronounced among patients with early-stage IPLC vs. advanced-stage IPLC (HR = 2.14 [95% CI = 2.08-2.20] vs. 1.43 [95% CI = 1.21-1.70], respectively; Pinteraction <0.001). Analysis using MEC data showed that the effect of SPLC on reduced survival was statistically significantly larger among persons who actively smoked at initial diagnosis vs. those who formerly or never smoked (HR = 2.31 [95% CI = 1.48-3.61] vs. 1.41 [95% CI = 0.98-2.03], respectively; Pinteraction=0.04).SPLC diagnosis is statistically significantly associated with decreased survival in SEER and MEC. Intensive surveillance targeting patients with early-stage IPLC and active smoking at IPLC diagnosis may lead to a larger survival benefit.

  View details for DOI 10.1093/jnci/djab224

  View details for PubMedID 34893871

• Impact of Low-Dose CT Screening for Primary Lung Cancer on Subsequent Risk of Brain Metastasis. Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer Su, C. C., Wu, J. T., Neal, J. W., Popat, R. A., Kurian, A. W., Backhus, L. M., Nagpal, S., Leung, A. N., Wakelee, H. A., Han, S. S. 2021

  Abstract

  Brain metastasis (BM) is one of the most common metastases from primary lung cancer (PLC). Recently, the National Lung Screening Trial (NLST) demonstrated the efficacy of low-dose computed tomography (LDCT) screening on LC mortality reduction. However, it remains unknown if early detection of PLC through LDCT may be potentially beneficial in reducing the risk of subsequent metastases. Our study aimed to investigate the impact of LDCT screening for PLC on the risk of developing BM after PLC diagnosis.We used NLST data to identify 1,502 participants who were diagnosed with PLC in 2002-2009 and have follow-up data for BM. Cause-specific competing risk regression was applied to evaluate an association between BM risk and the mode of PLC detection-i.e., LDCT screen-detected versus non-LDCT screen-detected. Subgroup analyses were conducted in early-stage PLC patients and those who underwent surgery for PLC.Of 1502 participants, 41.4% had PLC detected through LDCT-screening versus 58.6% detected through other methods, e.g., chest X-Ray or incidental detection. Patients whose PLC was detected with LDCT-screening had a significantly lower 3-year incidence of BM (6.5%) versus those without (11.9%), with a cause-specific hazard ratio (HR) of 0.53 (p=0.001), adjusting for PLC stage, histology, diagnosis age and smoking status. This significant reduction in BM risk among PLCs detected through LDCT-screening persisted in subgroups of early-stage PLC participants (HR 0.47, p=0.002) and those who underwent surgery (HR 0.37, p=0.001).Early detection of PLC using LDCT-screening is associated with lower risk of BM after PLC diagnosis based on a large population-based study.

  View details for DOI 10.1016/j.jtho.2021.05.010

  View details for PubMedID 34091050