Maria Teresa Landi's research while affiliated with National Institutes of Health and other places

Background: The association between duration of smoking abstinence before non-small-cell lung cancer (NSCLC) diagnosis and subsequent survival can influence public health messaging delivered in lung-cancer screening. We aimed to assess whether the duration of smoking abstinence before diagnosis of NSCLC is associated with improved survival. Methods: In this retrospective, pooled analysis of cohort studies, we used 26 cohorts participating in Clinical Outcomes Studies of the International Lung Cancer Consortium (COS-ILCCO) at 23 hospitals. 16 (62%) were from North America, six (23%) were from Europe, three (12%) were from Asia, and one (4%) was from South America. Patients enrolled were diagnosed between June 1, 1983, and Dec 31, 2019. Eligible patients had smoking data before NSCLC diagnosis, epidemiological data at diagnosis (obtained largely from patient questionnaires), and clinical information (retrieved from medical records). Kaplan-Meier curves and multivariable Cox models (ie, adjusted hazard ratios [aHRs]) were generated with individual, harmonised patient data from the consortium database. We estimated overall survival for all causes, measured in years from diagnosis date until the date of the last follow-up or death due to any cause and NSCLC-specific survival. Findings: Of 42 087 patients with NSCLC in the COS-ILCCO database, 21 893 (52·0%) of whom were male and 20 194 (48·0%) of whom were female, we excluded 4474 (10·6%) with missing data. Compared with current smokers (15 036 [40·0%] of 37 613), patients with 1-3 years of smoking abstinence before NSCLC diagnosis (2890 [7·7%]) had an overall survival aHR of 0·92 (95% CI 0·87-0·97), patients with 3-5 years of smoking abstinence (1114 [3·0%]) had an overall survival aHR of 0·90 (0·83-0·97), and patients with more than 5 years of smoking abstinence (10 841 [28·8%]) had an overall survival aHR of 0·90 (0·87-0·93). Improved NSCLC-specific survival was observed in 4301 (44%) of 9727 patients who had quit cigarette smoking and was significant at abstinence durations of more than 5 years (aHR 0·87, 95% CI 0·81-0·93). Results were consistent across age, sex, histology, and disease-stage distributions. Interpretation: In this large, pooled analysis of cohort studies across Asia, Europe, North America, and South America, overall survival was improved in patients with NSCLC whose duration of smoking abstinence before diagnosis was as short as 1 year. These findings suggest that quitting smoking can improve overall survival, even if NSCLC is diagnosed at a later lung-cancer screening visit. These findings also support the implementation of public health smoking cessation strategies at any time. Funding: The Alan B Brown Chair, The Posluns Family Fund, The Lusi Wong Fund, and the Princess Margaret Cancer Foundation.

Objectives Workers in the construction industry have been exposed to asbestos in various occupations. In Italy, a National Mesothelioma Registry has been implemented more than 20 years ago. Using cases selected from this registry and exploiting existing control data sets, we estimated relative risks for pleural mesothelioma (PM) among construction workers. Design Case–control study. Setting Cases from the National Mesothelioma Registry (2000–2018), controls from three previous case–control studies. Methods We selected male PM incident cases diagnosed in 2000–2018. Population controls were taken from three studies performed in six Italian regions within two periods (2002–2004 and 2012–2016). Age-adjusted and period-adjusted unconditional logistic regression models were fitted to estimate odds ratios (OR) for occupations in the construction industry. We followed two approaches, one (primary) excluding and the other (secondary) including subjects employed in other non-construction blue collar occupations for >5 years. For both approaches, we performed an overall analysis including all cases and, given the incomplete temporal and geographic overlap of cases and controls, three time or/and space restricted sensitivity analyses. Results The whole data set included 15 592 cases and 2210 controls. With the primary approach (4797 cases and 1085 controls), OR was 3.64 (2181 cases) for subjects ever employed in construction. We found elevated risks for blue-collar occupations (1993 cases, OR 4.52), including bricklayers (988 cases, OR 7.05), general construction workers (320 cases, OR 4.66), plumbers and pipe fitters (305 cases, OR 9.13), painters (104 cases, OR 2.17) and several others. Sensitivity analyses yielded very similar findings. Using the secondary approach, we observed similar patterns, but ORs were remarkably lower. Conclusions We found markedly increased PM risks for most occupations in the construction industry. These findings are relevant for compensation of subjects affected with mesothelioma in the construction industry.

In our previous work, we demonstrated that it is feasible to perform analysis on mutation signature data without the need for downloads or installations and analyze individual patient data at scale without compromising privacy. Building on this foundation, we developed a Software Development Kit (SDK) called mSigSDK to facilitate the orchestration of distributed data processing workflows and graphic visualization of mutational signature analysis results. We strictly adhered to modern web computing standards, particularly the modularization standards set by the ECMAScript ES6 framework (JavaScript modules). Our approach allows for computation to be entirely performed by secure delegation to the computational resources of the user's own machine (in-browser), without any downloads or installations. The mSigSDK was developed primarily as a companion library to the mSig Portal resource of the National Cancer Institute Division of Cancer Epidemiology and Genetics (NIH/NCI/DCEG), with a focus on its FAIR extensibility as components of other researchers' computational constructs. Anticipated extensions include the programmatic operation of other mutation signature API ecosystems such as SIGNAL and COSMIC, advancing towards a data commons for mutational signature research (Grossman et al., 2016).

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200 139 SNPs of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer GWAS. Discovery data included 18 082 cases and 13 780 controls of European ancestry. Replication data included 1914 cases and 3065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH (rs34577742 C > T, OR = 0.90, 95% CI = 0.89-0.93, P = 7.64x10-9) and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27x10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76x10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25x10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94x10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25x10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64x10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81x10-2). Subsequent TWAS using expression weights from a lung eQTL study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44x10-4) and SFTA2 (PTWAS = 2.32x10-6).

Background: Spitzoid morphology in familial melanoma has been associated with germline variants in POT1, a telomere maintenance gene (TMG), suggesting a link between telomere biology and spitzoid differentiation. Objective: To assess if familial melanoma cases associated with germline variants in TMG (POT1, ACD, TERF2IP, and TERT) commonly exhibit spitzoid morphology. Methods: In this case series, melanomas were classified as having spitzoid morphology if at least 3 of 4 dermatopathologists reported this finding in ≥25% of tumor cells. Logistic regression was used to calculate odds ratios (OR) of spitzoid morphology compared to familial melanomas from unmatched noncarriers that were previously reviewed by a National Cancer Institute dermatopathologist. Results: Spitzoid morphology was observed in 77% (23 of 30), 75% (3 of 4), 50% (2 of 4), and 50% (1 of 2) of melanomas from individuals with germline variants in POT1, TERF2IP, ACD, and TERT, respectively. Compared to noncarriers (n = 139 melanomas), POT1 carriers (OR = 225.1, 95% confidence interval: 51.7-980.5; P < .001) and individuals with TERF2IP, ACD, and TERT variants (OR = 82.4, 95% confidence interval: 21.3-494.6; P < .001) had increased odds of spitzoid morphology. Limitations: Findings may not be generalizable to nonfamilial melanoma cases. Conclusion: Spitzoid morphology in familial melanoma could suggest germline alteration of TMG.

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

Tumor mutational signatures are important in clinical decision-making and are typically analyzed using whole exome or genome sequencing (WES/WGS). However, targeted sequencing is more commonly used in clinical settings, posing challenges in mutational signature analysis due to sparse mutation data and non-overlapping targeted gene panels. We introduce SATS (Signature Analyzer for Targeted Sequencing), an analytical method that identifies mutational signatures in targeted sequenced tumors by analyzing tumor mutational burdens and accounting for different gene panels. We demonstrate through simulations and pseudo-targeted sequencing data (generated by down-sampling WES/WGS data) that SATS can accurately detect common mutational signatures with distinct profiles. Using SATS, we created a pan-cancer catalog of mutational signatures specifically tailored to targeted sequencing by analyzing 100,477 targeted sequenced tumors from the AACR Project GENIE. The catalog allows SATS to estimate signature activities even within a single sample, providing new opportunities for applying mutational signatures in clinical settings.

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B). However, how APOBEC3A/B interact with exogenous mutagenic processes in shaping tumor development is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence, apoptosis, and cell regeneration, as indicated by telomere shortening, high expression of pulmonary healing signaling pathway and stemness markers in HAS. The expected association of tobacco smoking exposure with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS tumors have slower clonal expansion and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells in HAS. These findings show how heterogeneity in mutational burden across competing mutational processes and cell types contributes to tumor development, with important clinical implications. Citation Format: Tongwu Zhang, Jian Sang, Phuc H. Hoang, Wei Zhao, Jennifer Rosenbaum, Leszek J. Klimczak, John McElderry, Alyssa Klein, Christopher Wirth, Erik N. Bergstrom, Marcos Díaz-Gay, Raviteja Vangara, Amy Hutchinson, Scott M. Lawrence, Nathan Cole, Bin Zhu, Teresa M. Przytycka, Jianxin Shi, Neil E. Caporaso, Robert Homer, Angela C. Pesatori, Dario Consonni, Stephen J. Chanock, David C. Wedge, Dmitry A. Gordenin, Ludmil B. Alexandrov, Reuben S. Harris, Maria Teresa Landi. APOBEC deaminases compete with tobacco smoking mutagenesis and affect age at onset of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1166.

Over the last few decades, next generation sequencing technologies, including whole genome sequencing (WGS), have been increasingly used in cancer genomics studies. However, there is no efficient way to manage, visualize and integratively analyze sample-level WGS results across different bioinformatic pipelines, particularly for non-bioinformaticians. This greatly limits the usability of WGS data for biological discovery. Following the FAIR principles (findability, accessibility, interoperability, and reusability), we developed Sherlock-Genome, a R Shiny app designed for data harmonization, visualization and integrative analyses for WGS-based cancer genomics studies. Specifically, Sherlock-Genome provides pipelines for WGS analyses coupled with detailed guidelines on data preparation. The users can download the pipelines on their local computer, run the analyses and then upload the sample-level results into the Sherlock-Genome for data harmonization and integrative analyses across different genomic features. Sherlock-Genome also implements rigorous WGS-related data QC steps based on NGSpurity, a workflow that estimates the tumor purity, ploidy and clonal architecture by integrating somatic copy number alterations (SCNA), single nucleotide variants (SNV) and cancer cell fraction. Currently, Sherlock-Genome includes a few independent modules that allow users to generate a variety of interactive data inspection and visualization images, and perform many integrative analyses also using clinical and epidemiological data. These modules include study information and sample-level data QC (study overview, manifest information, NGSpurity), summaries of major genomics alterations (mutations, SCNA, structural variants), reports of advanced genomics analyses (mutational signatures, genomic landscape, clonal evolution) and functions related to different types of integrative analyses (survival analysis, integrative analysis). In addition, all plots in the Sherlock-Genome app can be downloaded as publication-ready figures from each module. Sherlock-Genome can be deployed in both local and cloud environments, allowing users to share sample-level analytical results together with the related publications. Sherlock-Genome has the potential to be widely used in cancer genomics allowing sample-level integrative analyses across multiple WGS and additional multi-omics features. A Sherlock-Genome demo with major module functions could be presented to allow users to know about this new interactive user-friendly tool for data analysis and visualization that can greatly advance biological discoveries. Citation Format: Alyssa Klein, Maria Teresa Landi, Tongwu Zhang. Sherlock-Genome: a R shiny app for genomic analysis and visualization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2087.