Immune Checkpoint Inhibition and the Prevalence of Autoimmune Disorders Among Patients with Lung and Renal Cancer

PURPOSE: Immune checkpoint inhibition reactivates the immune response against cancer cells in multiple tissue types and has been shown to induce durable responses. However, for patients with autoimmune disorders, their conditions can worsen with this reactivation. We sought to identify, among patients with lung and renal cancer, how many harbor a comorbid autoimmune condition and may be at risk of worsening their condition while on immune checkpoint inhibitors such as nivolumab and pembrolizumab. METHODS: An administrative health care claims database, Truven MarketScan, was used to identify patients diagnosed with lung and renal cancer from 2010 to 2013. We assessed patients for diagnosis of autoimmune diseases 1 year prior to or after diagnosis of cancer using International Classification of Diseases, Ninth Revision codes for 41 autoimmune diseases. Baseline characteristics and other comorbid conditions were recorded. RESULTS: More than 25% of patients with both lung and renal cancer had a comorbid autoimmune condition between 2010 and 2013 and were more likely to be women, older, and have more baseline comorbidities. CONCLUSIONS: This population presents a dilemma to physicians when deciding to treat with immune checkpoint inhibitors and risk immune-related adverse events. Future evaluation of real-world use of immune checkpoint inhibitors in patients with cancer with autoimmune diseases will be needed

EXPLORING THE EFFECT OF CHRONIC INFLAMMATION ON RESPONSE TO IMMUNE CHECKPOINT INHIBITORS IN CANCER

Precision medicine has allowed for the development of monoclonal antibodies that unmask the anti-tumor immune response. These agents have provided some patients durable clinical benefit. However, PD-1 and PD-L1 inhibitor therapies are effective in a small group (10-20%) of non-small cell lung cancer (NSCLC) patients when used as single-agent therapy. The approved companion diagnostic is expression of the immune cell surface molecule, programmed death ligand 1 (PD-L1), on tumors measured by immunohistochemistry (IHC). Studies in tumor biology and immune surveillance dictate that PD-1 inhibitor efficacy should depend on the level of PD-L1 expression; however, the literature has not followed with convincing evidence. The limitations of this test include timing of tissue acquisition, tumor heterogeneity, and timing of therapy relative to the expression of PD-L1. In addition, the requirement of analyzing tumor tissue biopsy samples from a patient is cumbersome. Thus, a peripheral blood biomarker that predicts efficacy of PD-1/PD-L1 inhibition would be optimal for precise and cost-effective treatment. A history of chronic inflammatory diseases may be advantageous for a cancer patient who is treated with PD-1/PD-L1 inhibitors and may allow them to then mobilize a swift immune response to tumor cells. Specific biological components of this persistent inflammation may predict PD-1 inhibitor response. We have taken a novel approach to leverage national healthcare claims data that couples patient history with response to therapy. We have identified potential peripheral blood biomarkers of response to PD-1/PD-L1 inhibitors using a combination of healthcare outcomes and molecular markers that correlate with therapeutic efficacy

Statin Use and Venous Thromboembolism in Cancer: A Large, Active Comparator, Propensity Score Matched Cohort Study

Background—Statins have been shown to have a protective effect for venous thromboembolism (VTE) in the general population. This study sought to assess the association between statins and the risk for cancer-associated deep vein thrombosis (DVT) and pulmonary embolism (PE). Methods—Patients with newly diagnosed cancer were followed for up to one year in a healthcare claims database (2010–2013). Three treatment groups included statin users, non-statin cholesterol lowering medication users, and an untreated group with pre-existing indications for statin therapy (hyperlipidemia, diabetes, or heart disease). Propensity score matched groups were compared using competing risks survival models for DVT and PE outcomes reporting the hazard ratios (HR) between the treatment groups. Sensitivity analyses assessed the influence of age and individual medications. Results—The total cohort included 170,459 patients, which, after matching, were similar on baseline characteristics. The overall model showed a statistically significant protective effect for statins compared to no treatment attributed only to leukemia for DVT (HR = 0.77, 95% CI 0.61–0.99) and colorectal cancers for PE (HR = 0.80, 95% CI 0.64–0.99) in stratified analyses. There were generally no differences in outcomes between statins and non-statins and no individual statin use showed results different from the class effect. Conclusions—In this propensity score matched sample of patients with cancer, statins were shown to have a small protective effect in some cancers for DVT or PE compared to no treatment and little difference compared to an active control group. The lack of effect was consistent across statins and was also not found for any of the sensitivity analyses included

Landscape of KRASG12C, Associated Genomic Alterations, and Interrelation With Immuno-Oncology Biomarkers in KRAS-Mutated Cancers

Genomic alterations; Mutated cancers; Immuno-oncologyAlteraciones genómicas; Cánceres mutados; Inmuno-oncologíaAlteracions genòmiques; Càncers mutats; Immuno-oncologiaPURPOSE Promising single-agent activity from sotorasib and adagrasib in KRASG12C-mutant tumors has provided clinical evidence of effective KRAS signaling inhibition. However, comprehensive analysis of KRAS-variant prevalence, genomic alterations, and the relationship between KRAS and immuno-oncology biomarkers is lacking. MATERIALS AND METHODS Retrospective analysis of deidentified records from 79,004 patients with various cancers who underwent next-generation sequencing was performed. Fisher's exact test evaluated the association between cancer subtypes and KRAS variants. Logistic regression assessed KRASG12C comutations with other oncogenes and the association between KRAS variants and immuno-oncology biomarkers. RESULTS Of the 79,004 samples assessed, 13,758 (17.4%) harbored KRAS mutations, with 1,632 (11.9%) harboring KRASG12C and 12,126 (88.1%) harboring other KRAS variants (KRASnon-G12C). Compared with KRASnon-G12C across all tumor subtypes, KRASG12C was more prevalent in females (56% v 51%, false discovery rate-adjusted P value [FDR-P] = .0006), current or prior smokers (85% v 56%, FDR-P 60 years (73% v 63%, FDR-P ≤ .0001). The most frequent KRAS variants across all subtypes were G12D (29.5%), G12V (23.0%), G12C (11.9%), G13D (6.5%), and G12R (6.2%). KRASG12C was most prevalent in patients with non–small-cell lung cancer (9%), appendiceal (3.9%), colorectal (3.2%), tumor of unknown origin (1.6%), small bowel (1.43%), and pancreatic (1.3%) cancers. Compared with KRASnon-G12C-mutated, KRASG12C-mutated tumors were significantly associated with tumor mutational burden-high status (17.9% v 8.4%, odds ratio [OR] = 2.38; FDR-P < .0001). KRASG12C-mutated tumors exhibited a distinct comutation profile from KRASnon-G12C-mutated tumors, including higher comutations of STK11 (20.59% v 5.95%, OR = 4.10; FDR-P < .01) and KEAP1 (15.38% v 4.61%, OR = 3.76; FDR-P < .01). CONCLUSION This study presents the first large-scale, pan-cancer genomic characterization of KRASG12C. The KRASG12C mutation was more prevalent in females and older patients and appeared to be associated with smoking status. KRASG12C tumors exhibited a distinct comutation profile and were associated with tumor mutational burden-high status

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Immune Checkpoint Inhibition and the Prevalence of Autoimmune Disorders Among Patients With Lung and Renal Cancer

Purpose: Immune checkpoint inhibition reactivates the immune response against cancer cells in multiple tissue types and has been shown to induce durable responses. However, for patients with autoimmune disorders, their conditions can worsen with this reactivation. We sought to identify, among patients with lung and renal cancer, how many harbor a comorbid autoimmune condition and may be at risk of worsening their condition while on immune checkpoint inhibitors such as nivolumab and pembrolizumab. Methods: An administrative health care claims database, Truven MarketScan, was used to identify patients diagnosed with lung and renal cancer from 2010 to 2013. We assessed patients for diagnosis of autoimmune diseases 1 year prior to or after diagnosis of cancer using International Classification of Diseases, Ninth Revision codes for 41 autoimmune diseases. Baseline characteristics and other comorbid conditions were recorded. Results: More than 25% of patients with both lung and renal cancer had a comorbid autoimmune condition between 2010 and 2013 and were more likely to be women, older, and have more baseline comorbidities. Conclusions: This population presents a dilemma to physicians when deciding to treat with immune checkpoint inhibitors and risk immune-related adverse events. Future evaluation of real-world use of immune checkpoint inhibitors in patients with cancer with autoimmune diseases will be needed

Clinical, Genomic, and Transcriptomic Data Profiling of Biliary Tract Cancer Reveals Subtype-Specific Immune Signatures.

PurposeBiliary tract cancers (BTCs) are aggressive cancers that carry a poor prognosis. An enhanced understanding of the immune landscape of anatomically and molecularly defined subsets of BTC may improve patient selection for immunotherapy and inform immune-based combination treatment strategies.MethodsWe analyzed deidentified clinical, genomic, and transcriptomic data from the Tempus database to determine the mutational frequency and mutational clustering across the three major BTC subtypes (intrahepatic cholangiocarcinoma [IHC], extrahepatic cholangiocarcinoma, and gallbladder cancer). We subsequently determined the relationship between specific molecular alterations and anatomical subsets and features of the BTC immune microenvironment.ResultsWe analyzed 454 samples of BTC, of which the most commonly detected alterations were TP53 (42.5%), CDKN2A (23.4%), ARID1A (19.6%), BAP1 (15.5%), KRAS (15%), CDKN2B (14.2%), PBRM1 (11.7%), IDH1 (11.7%), TERT (8.4%), KMT2C (10.4%) and LRP1B (8.4%), and FGFR2 fusions (8.7%). Potentially actionable molecular alterations were identified in 30.5% of BTCs including 39.1% of IHC. Integrative cluster analysis revealed four distinct molecular clusters, with cluster 4 predominately associated with FGFR2 rearrangements and BAP1 mutations in IHC. Immune-related biomarkers indicative of an inflamed tumor-immune microenvironment were elevated in gallbladder cancers and in cluster 1, which was enriched for TP53, KRAS, and ATM mutations. Multiple common driver genes, including TP53, FGFR2, IDH1, TERT, BRAF, and BAP1, were individually associated with unique BTC immune microenvironments.ConclusionBTC subtypes exhibit diverse DNA alterations, RNA inflammatory signatures, and immune biomarkers. The association between specific BTC anatomical subsets, molecular alterations, and immunophenotypes highlights new opportunities for therapeutic development

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press