Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights.

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Synthetic PET from CT improves diagnosis and prognosis for lung cancer: Proof of concept.

[18F]Fluorodeoxyglucose positron emission tomography (FDG-PET) and computed tomography (CT) are indispensable components in modern medicine. Although PET can provide additional diagnostic value, it is costly and not universally accessible, particularly in low-income countries. To bridge this gap, we have developed a conditional generative adversarial network pipeline that can produce FDG-PET from diagnostic CT scans based on multi-center multi-modal lung cancer datasets (n = 1,478). Synthetic PET images are validated across imaging, biological, and clinical aspects. Radiologists confirm comparable imaging quality and tumor contrast between synthetic and actual PET scans. Radiogenomics analysis further proves that the dysregulated cancer hallmark pathways of synthetic PET are consistent with actual PET. We also demonstrate the clinical values of synthetic PET in improving lung cancer diagnosis, staging, risk prediction, and prognosis. Taken together, this proof-of-concept study testifies to the feasibility of applying deep learning to obtain high-fidelity PET translated from CT.

Clinical Benefit from Docetaxel +/- Ramucirumab Is Not Associated with Mutation Status in Metastatic Non-Small-Cell Lung Cancer Patients Who Progressed on Platinum Doublets and Immunotherapy.

Docetaxel +/- ramucirumab remains the standard-of-care therapy for patients with metastatic non-small-cell lung cancer (NSCLC) after progression on platinum doublets and immune checkpoint inhibitors (ICIs). The aim of our study was to investigate whether the cancer gene mutation status was associated with clinical benefits from docetaxel +/- ramucirumab. We also investigated whether platinum/taxane-based regimens offered a better clinical benefit in this patient population. A total of 454 patients were analyzed (docetaxel +/- ramucirumab n=381; platinum/taxane-based regimens n=73). Progression-free survival (PFS) and overall survival (OS) were compared among different subpopulations with different cancer gene mutations and between patients who received docetaxel +/- ramucirumab versus platinum/taxane-based regimens. Among patients who received docetaxel +/- ramucirumab, the top mutated cancer genes included TP53 (n=167), KRAS (n=127), EGFR (n=65), STK11 (n=32), ERBB2 (HER2) (n=26), etc. None of these cancer gene mutations or PD-L1 expression was associated with PFS or OS. Platinum/taxane-based regimens were associated with a significantly longer mQS (13.00 m, 95% Cl: 11.20-14.80 m versus 8.40 m, 95% Cl: 7.12-9.68 m, LogRank P=0.019) than docetaxel +/- ramcirumab. Key prognostic factors including age, histology, and performance status were not different between these two groups. In conclusion, in patients with metastatic NSCLC who have progressed on platinum doublets and ICIs, the clinical benefit from docetaxel +/- ramucirumab is not associated with the cancer gene mutation status. Platinum/taxane-based regimens may offer a superior clinical benefit over docetaxel +/- ramucirumab in this patient population.

Real-World Efficacy and Safety of Amivantamab for EGFR-Mutant NSCLC.

INTRODUCTION: Amivantamab-vmjw (amivantamab) is a bispecific EGFR/MET antibody approved for patients with advanced NSCLC with EGFR exon 20 insertion mutations, after prior therapy. Nevertheless, the benefits and safety of amivantamab in other EGFR-mutant lung cancer, with or without osimertinib, and with concurrent radiation therapy, are less known. METHODS: We queried the MD Anderson Lung Cancer GEMINI, Fred Hutchinson Cancer Research Center, University of California Davis Comprehensive Cancer Center, and Stanford Cancer Center's database for patients with EGFR-mutant NSCLC treated with amivantamab, not on a clinical trial. The data analyzed included initial response, duration of treatment, and concomitant radiation safety in overall population and prespecified subgroups. RESULTS: A total of 61 patients received amivantamab. Median age was 65 (31-81) years old; 72.1% were female; and 77% were patients with never smoking history. Median number of prior lines of therapies was four. On the basis of tumor's EGFR mutation, 39 patients were in the classical mutation cohort, 15 patients in the exon 20 cohort, and seven patients in the atypical cohort. There were 37 patients (58.7%) who received amivantamab concomitantly with osimertinib and 25 patients (39.1%) who received concomitant radiation. Furthermore, 54 patients were assessable for response in the overall population; 19 patients (45.2%) had clinical response and disease control rate (DCR) was 64.3%. In the classical mutation cohort of the 33 assessable patients, 12 (36.4%) had clinical response and DCR was 48.5%. In the atypical mutation cohort, six of the seven patients (85.7%) had clinical response and DCR was 100%. Of the 13 assessable patients in the exon 20 cohort, five patients (35.7%) had clinical response and DCR was 64.3%. Adverse events reported with amivantamab use were similar as previously described in product labeling. No additional toxicities were noted when amivantamab was given with radiation with or without osimertinib. CONCLUSIONS: Our real-world multicenter analysis revealed that amivantamab is a potentially effective treatment option for patients with EGFR mutations outside of exon 20 insertion mutations. The combination of osimertinib with amivantamab is safe and feasible. Radiation therapy also seems safe when administered sequentially or concurrently with amivantamab.

Automated Cellular-Level Dual Global Fusion of Whole-Slide Imaging for Lung Adenocarcinoma Prognosis.

Histopathologic whole-slide images (WSI) are generally considered the gold standard for cancer diagnosis and prognosis. Survival prediction based on WSI has recently attracted substantial attention. Nevertheless, it remains a central challenge owing to the inherent difficulties of predicting patient prognosis and effectively extracting informative survival-specific representations from WSI with highly compounded gigapixels. In this study, we present a fully automated cellular-level dual global fusion pipeline for survival prediction. Specifically, the proposed method first describes the composition of different cell populations on WSI. Then, it generates dimension-reduced WSI-embedded maps, allowing for efficient investigation of the tumor microenvironment. In addition, we introduce a novel dual global fusion network to incorporate global and inter-patch features of cell distribution, which enables the sufficient fusion of different types and locations of cells. We further validate the proposed pipeline using The Cancer Genome Atlas lung adenocarcinoma dataset. Our model achieves a C-index of 0.675 (±0.05) in the five-fold cross-validation setting and surpasses comparable methods. Further, we extensively analyze embedded map features and survival probabilities. These experimental results manifest the potential of our proposed pipeline for applications using WSI in lung adenocarcinoma and other malignancies.

ATM Mutations Associate with Distinct Co-Mutational Patterns and Therapeutic Vulnerabilities in NSCLC.

PURPOSE: Ataxia-telangiectasia mutated (ATM) is the most frequently mutated DNA damage repair gene in non-small cell lung cancer (NSCLC). However, the molecular correlates of ATM mutations and their clinical implications have not been fully elucidated. EXPERIMENTAL DESIGN: Clinicopathologic and genomic data from 26,587 patients with NSCLC from MD Anderson, public databases, and a de-identified nationwide (US-based) NSCLC clinicogenomic database (CGDB) were used to assess the co-mutation landscape, protein expression, and mutational processes in ATM-mutant tumors. We used the CGDB to evaluate ATM-associated outcomes in patients treated with immune checkpoint inhibitors (ICI) with or without chemotherapy, and assessed the effect of ATM loss on STING signaling and chemotherapy sensitivity in preclinical models. RESULTS: Nonsynonymous mutations in ATM were observed in 11.2% of samples (2,980/26,587) and were significantly associated with mutations in KRAS, but mutually exclusive with EGFR (q < 0.1). KRAS mutational status constrained the ATM co-mutation landscape, with strong mutual exclusivity with TP53 and KEAP1 within KRAS-mutated samples. Those ATM mutations that co-occurred with TP53 were more likely to be missense mutations and associate with high mutational burden, suggestive of non-functional passenger mutations. In the CGDB cohort, dysfunctional ATM mutations associated with improved OS only in patients treated with ICI-chemotherapy, and not ICI alone. In vitro analyses demonstrated enhanced upregulation of STING signaling in ATM knockout cells with the addition of chemotherapy. CONCLUSIONS: ATM mutations define a distinct subset of NSCLC associated with KRAS mutations, increased TMB, decreased TP53 and EGFR co-occurrence, and potential increased sensitivity to ICIs in the context of DNA-damaging chemotherapy.

Pathomic Features Reveal Immune and Molecular Evolution From Lung Preneoplasia to Invasive Adenocarcinoma.

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

Brief Report: Clinical Response, Toxicity, and Resistance Mechanisms to Osimertinib Plus MET Inhibitors in Patients With EGFR-Mutant MET-Amplified NSCLC.

Introduction: MET amplification is a known resistance mechanism to EGFR tyrosine kinase inhibitor (TKI) treatment in EGFR-mutant NSCLC. Dual EGFR-MET inhibition has been reported with success in overcoming such resistance and inducing clinical benefit. Resistance mechanisms to dual EGFR-MET inhibition require further investigation and characterization. Methods: Patients with NSCLC with both MET amplification and EGFR mutation who have received crizotinib, capmatinib, savolitinib, or tepotinib plus osimertinib (OSI) after progression on OSI at MD Anderson Cancer Center were included in this study. Molecular profiling was completed by means of fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS). Radiological response was assessed on the basis of Response Evaluation Criteria in Solid Tumors version 1.1. Results: From March 2016 to March 2022, 23 treatments with dual MET inhibitor and osi were identified with a total of 20 patients included. Three patients received capmatinib plus OSI after progression on crizotinib plus OSI. Median age was 64 (38-89) years old and 75% were female. MET amplification was detected by FISH in 14 patients in the tissue, NGS in 10 patients, and circulating tumor DNA in three patients. Median MET gene copy number was 13.6 (6.4-20). Overall response rate was 34.8% (eight of 23). In assessable patients, tumor shrinkage was observed in 82.4% (14 of 17). Median time on treatment was 27 months. Two of three patients responded to capmatinib plus OSI after progression on crizotinib plus OSI. Dual EGFR-MET inhibition was overall well tolerated. Two patients on crizotinib plus OSI and one pt on capmatinib plus OSI discontinued therapy due to pneumonitis. One pt discontinued crizotinib plus OSI due to gastrointestinal toxicity. Six patients were still on double TKI treatment. At disease progression to dual EGFR-MET inhibition, FISH and NGS on tumor and plasma were completed in six patients. Notable resistance mechanisms observed include acquired MET D1246H (n = 1), acquired EGFR C797S (n = 2), FGFR2 fusion (n = 1, concurrent with C797S), and EGFR G796S (n = 1, concurrent with C797S). Four patients lost MET amplification. Conclusions: Dual EGFR and MET inhibition yielded high clinical response rate after progression on OSI. Resistance mechanisms to EGFR-MET double TKI inhibition include MET secondary mutation, EGFR secondary mutation, or loss of MET amplification.

Clinical and Molecular Features of Long-term Response to Immune Checkpoint Inhibitors in Patients with Advanced Non-Small Cell Lung Cancer.

PURPOSE: We sought to identify features of patients with advanced non-small cell lung cancer (NSCLC) who achieve long-term response (LTR) to immune checkpoint inhibitors (ICI), and how these might differ from features predictive of short-term response (STR). EXPERIMENTAL DESIGN: We performed a multicenter retrospective analysis of patients with advanced NSCLC treated with ICIs between 2011 and 2022. LTR and STR were defined as response ≥ 24 months and response < 12 months, respectively. Tumor programmed death ligand 1 (PD-L1) expression, tumor mutational burden (TMB), next-generation sequencing (NGS), and whole-exome sequencing (WES) data were analyzed to identify characteristics enriched in patients achieving LTR compared with STR and non-LTR. RESULTS: Among 3,118 patients, 8% achieved LTR and 7% achieved STR, with 5-year overall survival (OS) of 81% and 18% among LTR and STR patients, respectively. High TMB (≥50th percentile) enriched for LTR compared with STR (P = 0.001) and non-LTR (P < 0.001). Whereas PD-L1 ≥ 50% enriched for LTR compared with non-LTR (P < 0.001), PD-L1 ≥ 50% did not enrich for LTR compared with STR (P = 0.181). Nonsquamous histology (P = 0.040) and increasing depth of response [median best overall response (BOR) -65% vs. -46%, P < 0.001] also associated with LTR compared with STR; no individual genomic alterations were uniquely enriched among LTR patients. CONCLUSIONS: Among patients with advanced NSCLC treated with ICIs, distinct features including high TMB, nonsquamous histology, and depth of radiographic improvement distinguish patients poised to achieve LTR compared with initial response followed by progression, whereas high PD-L1 does not.

Predicting benefit from immune checkpoint inhibitors in patients with non-small-cell lung cancer by CT-based ensemble deep learning: a retrospective study.

BACKGROUND: Only around 20-30% of patients with non-small-cell lung cancer (NCSLC) have durable benefit from immune-checkpoint inhibitors. Although tissue-based biomarkers (eg, PD-L1) are limited by suboptimal performance, tissue availability, and tumour heterogeneity, radiographic images might holistically capture the underlying cancer biology. We aimed to investigate the application of deep learning on chest CT scans to derive an imaging signature of response to immune checkpoint inhibitors and evaluate its added value in the clinical context. METHODS: In this retrospective modelling study, 976 patients with metastatic, EGFR/ALK negative NSCLC treated with immune checkpoint inhibitors at MD Anderson and Stanford were enrolled from Jan 1, 2014, to Feb 29, 2020. We built and tested an ensemble deep learning model on pretreatment CTs (Deep-CT) to predict overall survival and progression-free survival after treatment with immune checkpoint inhibitors. We also evaluated the added predictive value of the Deep-CT model in the context of existing clinicopathological and radiological metrics. FINDINGS: Our Deep-CT model demonstrated robust stratification of patient survival of the MD Anderson testing set, which was validated in the external Stanford set. The performance of the Deep-CT model remained significant on subgroup analyses stratified by PD-L1, histology, age, sex, and race. In univariate analysis, Deep-CT outperformed the conventional risk factors, including histology, smoking status, and PD-L1 expression, and remained an independent predictor after multivariate adjustment. Integrating the Deep-CT model with conventional risk factors demonstrated significantly improved prediction performance, with overall survival C-index increases from 0·70 (clinical model) to 0·75 (composite model) during testing. On the other hand, the deep learning risk scores correlated with some radiomics features, but radiomics alone could not reach the performance level of deep learning, indicating that the deep learning model effectively captured additional imaging patterns beyond known radiomics features. INTERPRETATION: This proof-of-concept study shows that automated profiling of radiographic scans through deep learning can provide orthogonal information independent of existing clinicopathological biomarkers, bringing the goal of precision immunotherapy for patients with NSCLC closer. FUNDING: National Institutes of Health, Mark Foundation Damon Runyon Foundation Physician Scientist Award, MD Anderson Strategic Initiative Development Program, MD Anderson Lung Moon Shot Program, Andrea Mugnaini, and Edward L C Smith.

MET Amplification as a Resistance Driver to TKI Therapies in Lung Cancer: Clinical Challenges and Opportunities.

Targeted therapy has emerged as an important pillar for the standard of care in oncogene-driven non-small cell lung cancer (NSCLC), which significantly improved outcomes of patients whose tumors harbor oncogenic driver mutations. However, tumors eventually develop resistance to targeted drugs, and mechanisms of resistance can be diverse. MET amplification has been proven to be a driver of resistance to tyrosine kinase inhibitor (TKI)-treated advanced NSCLC with its activation of EGFR, ALK, RET, and ROS-1 alterations. The combined therapy of MET-TKIs and EGFR-TKIs has shown outstanding clinical efficacy in EGFR-mutated NSCLC with secondary MET amplification-mediated resistance in a series of clinical trials. In this review, we aimed to clarify the underlying mechanisms of MET amplification-mediated resistance to tyrosine kinase inhibitors, discuss the ways and challenges in the detection and diagnosis of MET amplifications in patients with metastatic NSCLC, and summarize the recently published clinical data as well as ongoing trials of new combination strategies to overcome MET amplification-mediated TKI resistance.

Efficacy and clinicogenomic correlates of response to immune checkpoint inhibitors alone or with chemotherapy in non-small cell lung cancer.

The role of combination chemotherapy with immune checkpoint inhibitors (ICI) (ICI-chemo) over ICI monotherapy (ICI-mono) in non-small cell lung cancer (NSCLC) remains underexplored. In this retrospective study of 1133 NSCLC patients, treatment with ICI-mono vs ICI-chemo associate with higher rates of early progression, but similar long-term progression-free and overall survival. Sequential vs concurrent ICI and chemotherapy have similar long-term survival, suggesting no synergism from combination therapy. Integrative modeling identified PD-L1, disease burden (Stage IVb; liver metastases), and STK11 and JAK2 alterations as features associate with a higher likelihood of early progression on ICI-mono. CDKN2A alterations associate with worse long-term outcomes in ICI-chemo patients. These results are validated in independent external (n = 89) and internal (n = 393) cohorts. This real-world study suggests that ICI-chemo may protect against early progression but does not influence overall survival, and nominates features that identify those patients at risk for early progression who may maximally benefit from ICI-chemo.

HRAS Mutations Define a Distinct Subgroup in Head and Neck Squamous Cell Carcinoma.

PURPOSE: In head and neck squamous cell carcinoma (HNSCC), HRAS mutation is a new actionable oncogene driver. We aimed to evaluate HRAS mutational variants, comutation profile, and survival outcomes of this molecularly defined population. METHODS: We leveraged four deidentified patient data sets with HRAS-mutant HNSCC, MD Anderson Cancer Center, Kura Oncology, Inc trial, Foundation Medicine, and American Association for Cancer Research GENIE v.12. Patient demographic information and clinical courses were extracted, when available, in addition to HRAS mutation type and co-occurring mutations. Survival outcomes were analyzed (Kaplan-Meier method). RESULTS: Two hundred forty-nine patients with HRAS-mutant HNSCC were identified from the four data sets. Median age ranged from 55 to 65 years, with a higher frequency in male patients (64%); the majority of HRAS-mutant HNSCC occurred in human papillomavirus-negative HNSCC. HRAS mutation patterns were similar across data sets; G12S was the most common (29%). Treatment responses to tipifarnib were not codon-specific. Compared with wild-type, significantly co-occurring mutations with HRAS were Casp8 (Fisher's exact test, P < .00013), TERT (P < .0085), and NOTCH1 (P < .00013). Analysis of clinical courses from the MD Anderson Cancer Center and Kura Oncology, Inc data sets demonstrated poor clinical outcomes with a high rate of recurrence following primary definitive treatment (50%-67% relapse < 6 months) and short disease-free survival (4.0 months; 95% CI, 1.0 to 36.0) and overall survival (OS; 15.0 months; 95% CI, 6.0 to 52.0). Use of tipifarnib in this data set demonstrated improved OS (25.5 months; 95% CI, 18.0 to 48.0). CONCLUSION: Oncogenic mutations in HRAS occur in 3%-4% of HNSCC, with G12S being the most frequent. Without targeted therapy, patients with HRAS-mutant HNSCC had poor clinic outcomes; observable trend toward improvement in OS has been noted in cohorts receiving treatments such as tipifarnib. The comutation pattern of HRAS-mutant in HNSCC is distinct, which may provide insight to future therapeutic combination strategies.

Limited Benefit from the Addition of Immunotherapy to Chemotherapy in TKI-Refractory EGFR-Mutant Lung Adenocarcinoma.

BACKGROUND: The benefit of chemotherapy combined with immunotherapy in EGFR-mutant lung adenocarcinoma (LUAD) patients whose tumor developed resistance to EGFR tyrosine kinase inhibitors (TKIs) is not thoroughly investigated. The goal of this retrospective cohort study is to assess the clinical efficiency of immunotherapy alone or in combination with chemotherapy in a real-world setting. METHODS: This retrospective cohort study enrolled LUAD patients with EGFR sensitive mutations whose tumor had acquired resistance to EGFR TKIs and received systemic treatment with chemotherapy (chemo; n = 84), chemotherapy combined with immunotherapy (chemoIO; n = 30), chemotherapy plus bevacizumab with or without IO (withBev; n = 42), and IO monotherapy (IO-mono; n = 22). Clinical progression-free survival (PFS) and overall survival (OS) were evaluated. Associations of clinical characteristics with outcomes were assessed using univariable and multi-covariate Cox Proportional Hazards regression models. RESULTS: A total of 178 patients (median age = 63.3; 57.9% females) with a median follow-up time of 42.0 (Interquartile range: 22.9-67.8) months were enrolled. There was no significant difference in PFS between chemoIO vs. chemo groups (5.3 vs. 4.8 months, p = 0.8). Compared to the chemo group, patients who received withBev therapy trended towards better PFS (6.1 months vs. 4.8; p = 0.3; HR 0.79; 95% CI: 0.52-1.20), while patients treated with IO-mono had inferior PFS (2.2 months; p = 0.001; HR 2.22; 95% CI: 1.37-3.59). Furthermore, PD-L1 level was not associated with PFS benefit in the chemoIO group. Patients with EGFR-mutant LUAD with high PD-L1 (≥50%) had shorter PFS (5.8 months) than non-EGFR/ALK LUAD patients who received chemoIO (12.8 months, p = 0.002; HR 0.22; 95% CI: 0.08-0.56) as first-line treatment. Chemotherapy-based therapy rendered similar benefit to patients with either EGFR exon19 deletion vs. L858R in the LUAD. CONCLUSIONS: This retrospective analysis revealed that immunotherapy provided limited additional benefit to chemotherapy in TKI-refractory EGFR-mutant LUAD. Chemotherapy alone or combined with bevacizumab remain good choices for patients with actionable EGFR mutations.

Immunogenomic intertumor heterogeneity across primary and metastatic sites in a patient with lung adenocarcinoma.

BACKGROUND: Lung cancer is the leading cause of cancer death, partially owing to its extensive heterogeneity. The analysis of intertumor heterogeneity has been limited by an inability to concurrently obtain tissue from synchronous metastases unaltered by multiple prior lines of therapy. METHODS: In order to study the relationship between genomic, epigenomic and T cell repertoire heterogeneity in a rare autopsy case from a 32-year-old female never-smoker with left lung primary late-stage lung adenocarcinoma (LUAD), we did whole-exome sequencing (WES), DNA methylation and T cell receptor (TCR) sequencing to characterize the immunogenomic landscape of one primary and 19 synchronous metastatic tumors. RESULTS: We observed heterogeneous mutation, methylation, and T cell patterns across distinct metastases. Only TP53 mutation was detected in all tumors suggesting an early event while other cancer gene mutations were later events which may have followed subclonal diversification. A set of prevalent T cell clonotypes were completely excluded from left-side thoracic tumors indicating distinct T cell repertoire profiles between left-side and non left-side thoracic tumors. Though a limited number of predicted neoantigens were shared, these were associated with homology of the T cell repertoire across metastases. Lastly, ratio of methylated neoantigen coding mutations was negatively associated with T-cell density, richness and clonality, suggesting neoantigen methylation may partially drive immunosuppression. CONCLUSIONS: Our study demonstrates heterogeneous genomic and T cell profiles across synchronous metastases and how restriction of unique T cell clonotypes within an individual may differentially shape the genomic and epigenomic landscapes of synchronous lung metastases.

Diminished Efficacy of Programmed Death-(Ligand)1 Inhibition in STK11- and KEAP1-Mutant Lung Adenocarcinoma Is Affected by KRAS Mutation Status.

INTRODUCTION: STK11 and KEAP1 mutations (STK11 mutant [STK11MUT] and KEAP1MUT) are among the most often mutated genes in lung adenocarcinoma (LUAD). Although STK11MUT has been associated with resistance to programmed death-(ligand)1 (PD-[L]1) inhibition in KRASMUT LUAD, its impact on immunotherapy efficacy in KRAS wild-type (KRASWT) LUAD is currently unknown. Whether KEAP1MUT differentially affects outcomes to PD-(L)1 inhibition in KRASMUT and KRASWT LUAD is also unknown. METHODS: Clinicopathologic and genomic data were collected from September 2013 to September 2020 from patients with advanced LUAD at the Dana-Farber Cancer Institute/Massachusetts General Hospital cohort and the Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center cohort. Clinical outcomes to PD-(L)1 inhibition were analyzed according to KRAS, STK11, and KEAP1 mutation status in two independent cohorts. The Cancer Genome Atlas transcriptomic data were interrogated to identify differences in tumor gene expression and tumor immune cell subsets, respectively, according to KRAS/STK11 and KRAS/KEAP1 comutation status. RESULTS: In the combined cohort (Dana-Farber Cancer Institute/Massachusetts General Hospital + Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center) of 1261 patients (median age = 61 y [range: 22-92], 708 women [56.1%], 1065 smokers [84.4%]), KRAS mutations were detected in 536 cases (42.5%), and deleterious STK11 and KEAP1 mutations were found in 20.6% (260 of 1261) and 19.2% (231 of 1202) of assessable cases, respectively. In each independent cohort and in the combined cohort, STK11 and KEAP1 mutations were associated with significantly worse progression-free (STK11 hazard ratio [HR] = 2.04, p < 0.0001; KEAP1 HR = 2.05, p < 0.0001) and overall (STK11 HR = 2.09, p < 0.0001; KEAP1 HR = 2.24, p < 0.0001) survival to immunotherapy uniquely among KRASMUT but not KRASWT LUADs. Gene expression ontology and immune cell enrichment analyses revealed that the presence of STK11 or KEAP1 mutations results in distinct immunophenotypes in KRASMUT, but not in KRASWT, lung cancers. CONCLUSIONS: STK11 and KEAP1 mutations confer worse outcomes to immunotherapy among patients with KRASMUT but not among KRASWT LUAD. Tumors harboring concurrent KRAS/STK11 and KRAS/KEAP1 mutations display distinct immune profiles in terms of gene expression and immune cell infiltration.

Habitat Imaging Biomarkers for Diagnosis and Prognosis in Cancer Patients Infected with COVID-19.

OBJECTIVES: Cancer patients have worse outcomes from the COVID-19 infection and greater need for ventilator support and elevated mortality rates than the general population. However, previous artificial intelligence (AI) studies focused on patients without cancer to develop diagnosis and severity prediction models. Little is known about how the AI models perform in cancer patients. In this study, we aim to develop a computational framework for COVID-19 diagnosis and severity prediction particularly in a cancer population and further compare it head-to-head to a general population. METHODS: We have enrolled multi-center international cohorts with 531 CT scans from 502 general patients and 420 CT scans from 414 cancer patients. In particular, the habitat imaging pipeline was developed to quantify the complex infection patterns by partitioning the whole lung regions into phenotypically different subregions. Subsequently, various machine learning models nested with feature selection were built for COVID-19 detection and severity prediction. RESULTS: These models showed almost perfect performance in COVID-19 infection diagnosis and predicting its severity during cross validation. Our analysis revealed that models built separately on the cancer population performed significantly better than those built on the general population and locked to test on the cancer population. This may be because of the significant difference among the habitat features across the two different cohorts. CONCLUSIONS: Taken together, our habitat imaging analysis as a proof-of-concept study has highlighted the unique radiologic features of cancer patients and demonstrated effectiveness of CT-based machine learning model in informing COVID-19 management in the cancer population.

Landscape and Clonal Dominance of Co-occurring Genomic Alterations in Non-Small-Cell Lung Cancer Harboring MET Exon 14 Skipping.

MET exon 14 skipping alterations (METex14) comprise a diverse set of actionable oncogene drivers in non-small-cell lung cancer (NSCLC). Recent studies have established the efficacy of tyrosine kinase inhibitors for this patient population. The landscape of co-occurring genetic alterations in METex14 NSCLC and their potential impact to therapeutic sensitivities has not yet been fully described. MATERIALS AND METHODS: METex14 NSCLC cases were collected from three cohorts: the VISION trial, and data sets from Guardant360 and GenePlus. Clinicopathologic characteristics and METex14 mutation sites were analyzed and compared across data sets. Co-occurring genetic alterations and the clonality relationships to METex14 were evaluated. RESULTS: Of 40,824 NSCLCs, 692 METex14 cases (1.7%) were identified, including 332 in Guardant360, 188 in VISION, and 172 in GenePlus. The demographics and mutation type and/or sites were similar in the Asian versus Western cohorts. MET amplification, which were found to be associated with sensitivity to MET kinase inhibitors, co-occurs in 7.6%-13.8% of cases, whereas kinase domain secondary mutation of MET co-occurs in 5%-6%. When co-occurring with METex14, EGFR mutations were often identified as the dominant clone (78%, 7 of 9), whereas when co-occurring, METex14 (39%, 7 of 18) and KRAS (44%, 8 of 18) had similar rates of clonal dominance. PIK3CA and PTEN mutations were almost always subclones (89%, 16 of 18) to METex14. Moreover, RET-CCDC6 fusion and EGFR mutation were detected following crizotinib treatment in two patients, suggesting novel mechanisms of resistance. CONCLUSION: METex14 mutations frequently co-occur with other potential driver oncogenes with differing patterns of clonal dominance observed among the drivers. This cellular context can provide insights into whether METex14 is acting as a primary oncogenic driver or resistance mechanism and help guide treatment choices.

Application of Artificial Intelligence in Emergency Nursing of Patients with Chronic Obstructive Pulmonary Disease.

The research achievements of artificial intelligence technology in the development of chronic obstructive pulmonary disease were explored, and the advantages and problems encountered in the development of intelligent nursing were analyzed. This paper presents the application of artificial intelligence in the emergency care of patients with chronic obstructive pulmonary disease. The method included 447 COPD patients in a randomized controlled trial to observe the improvement of quality of life at 4 and 12 months after artificial intelligence medical intervention. A prospective randomized controlled trial included 101 patients with COPD who underwent a 9-month web-based knowledge exercise on the prevention of acute exacerbation of COPD through artificial intelligence medicine and were randomly divided into two groups: the experimental group and the control group. The results show that, in the experimental group and the control group, after 4 months, the quality of life does not change; after 12 months, compared with controls, the quality of life and emotional and psychological conditions have improved obviously. 29 patients who participated in the experiment and were randomly divided into the experimental group and the control group showed satisfactory results. COPD hospitalized rate and length of hospital stay were decreased in the experimental group than in the control group. For single-factor analysis, artificial intelligence medical intervention has not achieved significant significance, and the experimental results have preliminarily confirmed the effectiveness of artificial intelligence medical treatment.

Efficacy of Targeted Inhibitors in Metastatic Lung Squamous Cell Carcinoma With EGFR or ALK Alterations.

INTRODUCTION: The efficacy of targeted therapies in oncogene-driven lung adenocarcinomas (LUADs) has been well established; however, the benefit for EGFR-mutant or ALK-rearranged lung squamous cell carcinomas (LUSCs) is less known, partially owing to the rarity of the incidence. METHODS: We reviewed the database of the MD Anderson Cancer Center and identified metastatic LUSC with classic EGFR or ALK alterations. RESULTS: There were eight patients with EGFR-mutant LUSC (median age = 58 y) and six patients with EML4-ALK LUSC (median age = 50 y) who received tyrosine kinase inhibitors (TKIs) that were identified. Of the 14 patients, 11 (79%) were females and 12 (86%) were never smokers, similar to the demographics of EGFR or ALK LUAD. With TKI treatment, seven of eight cases of EGFR LUSC and four of six cases of ALK LUSC achieved partial response or stable disease, but the progression-free survival was 4.9 months and 2.9 months for EGFR-mutant and ALK-rearranged LUSC, respectively. In addition, we compared comutation profile of EGFR-mutant LUAD (The Cancer Genome Atlas, n = 46) versus LUSC (n = 19) and found that the comutation patterns are more consistent with squamous disease with a higher incidence of PIK3CA (p = 0.02) and KRAS or BRAF (p = 0.04) alterations. CONCLUSIONS: EGFR or ALK alterations occur in patients with LUSC, especially never-smoker females. TKI treatments render clinical benefit in disease control, but the duration was considerably truncated compared with those historically observed in LUAD.