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Background: While functional connectivity is widely studied, there has been little work studying functional connectivity at different spatial scales. Likewise, the relationship of functional connec...

Over the past decade, multiple trials, including the precision medicine trial National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH, EAY131, NCT02465060) have sought to determine if treating cancer based on specific genomic alterations is effective, irrespective of the cancer histology. Although many therapies are now approved for the treatment of cancers harboring specific genomic alterations, most patients do not respond to therapies targeting a single alteration. Further, when antitumor responses do occur, they are often not durable due to the development of drug resistance. Therefore, there is a great need to identify rational combination therapies that may be more effective. To address this need, the NCI and National Clinical Trials Network have developed NCI-ComboMATCH, the successor to NCI-MATCH. Like the original trial, NCI-ComboMATCH is a signal-seeking study. The goal of ComboMATCH is to overcome drug resistance to single-agent therapy and/or utilize novel synergies to increase efficacy by developing genomically-directed combination therapies, supported by strong preclinical in vivo evidence. Although NCI-MATCH was mainly comprised of multiple single-arm studies, NCI-ComboMATCH tests combination therapy, evaluating both combination of targeted agents as well as combinations of targeted therapy with chemotherapy. Although NCI-MATCH was histology agnostic with selected tumor exclusions, ComboMATCH has histology-specific and histology-agnostic arms. Although NCI-MATCH consisted of single-arm studies, ComboMATCH utilizes single-arm as well as randomized designs. NCI-MATCH had a separate, parallel Pediatric MATCH trial, whereas ComboMATCH will include children within the same trial. We present rationale, scientific principles, study design, and logistics supporting the ComboMATCH study.

BACKGROUND: This study had aimed to describe long-term decision regret, bowel dysfunction, and the overall quality of life in patients with diverticulitis, and to determine if elective colectomy was associated with these patient-reported outcome measures. METHODS: This mixed-methods, survey-based study was administered to a national cohort of patients in the United States with diverticulitis. We measured decision regret (Brehaut Decision Regret), bowel dysfunction (Low Anterior Resection Syndrome score), and the overall quality of life (EuroQol 5 Dimension) in this population. We asked open-ended questions to elucidate factors that influenced patients’ choices between elective colectomy and observation. RESULTS: Among the 614 respondents, 294 (48%) chose between colectomy and observational management, 94 (15%) had surgery, and 157 (26%) had major Low Anterior Resection Syndrome. Of the 294 that chose between colectomy and observational management, 51 (17%) experienced decision regret. Colectomy was associated with an average decrease in the Brehaut Decision Regret score by 6 points but was not associated with a categorical measure of decision regret (Brehaut Score ≥50). Bowel dysfunction and overall quality of life were not significantly associated with colectomy. Disease-related factors, psychosocial factors, and interactions with physicians were commonly cited as reasons for pursuing colectomy or observational management. CONCLUSION: Patients with self-reported diverticulitis describe high levels of decision regret and bowel dysfunction regardless of chosen management strategy. Physicians should be aware that psychosocial factors can strongly influence a patient’s choice between colectomy and observational management. We advocated for future prospective studies using patient reported outcome metrics to improve outcomes in diverticulitis.

TP53 mutation is the most frequent genetic event in head and neck squamous cell carcinoma (HNSCC), found in more than 80% of patients with human papillomavirus–negative disease. As mutations in the TP53 gene are associated with worse outcomes in HNSCC, novel therapeutic approaches are needed for patients with TP53-mutated tumors. The National Cancer Institute sponsored a Clinical Trials Planning Meeting to address the issues of identifying and developing clinical trials for patients with TP53 mutations. Subcommittees, or breakout groups, were tasked with developing clinical studies in both the locally advanced and recurrent and/or metastatic (R/M) disease settings as well as considering signal-seeking trial designs. A fourth breakout group was focused on identifying and standardizing biomarker integration into trial design; this information was provided to the other breakout groups prior to the meeting to aid in study development. A total of 4 concepts were prioritized to move forward for further development and implementation. This article summarizes the proceedings of the Clinical Trials Planning Meeting with the goal of developing clinical trials for patients with TP53-mutant HNSCC that can be conducted within the National Clinical Trials Network.

Impaired DNA repair activity has been shown to greatly increase rates of cancer clinically. It has been hypothesized that upregulating repair activity in susceptible individuals may be a useful strategy for inhibiting tumorigenesis. Here, we report that selected tyrosine kinase (TK) inhibitors including nilotinib, employed clinically in the treatment of chronic myeloid leukemia, are activators of the repair enzyme Human MutT Homolog 1 (MTH1). MTH1 cleanses the oxidatively damaged cellular nucleotide pool by hydrolyzing the oxidized nucleotide 8-oxo-2'-deoxyguanosine (8-oxo-dG)TP, which is a highly mutagenic lesion when incorporated into DNA. Structural optimization of analogues of TK inhibitors resulted in compounds such as SU0448, which induces 1000 ± 100% activation of MTH1 at 10 μM and 410 ± 60% at 5 μM. The compounds are found to increase the activity of the endogenous enzyme, and at least one (SU0448) decreases levels of 8-oxo-dG in cellular DNA. The results suggest the possibility of using MTH1 activators to decrease the frequency of mutagenic nucleotides entering DNA, which may be a promising strategy to suppress tumorigenesis in individuals with elevated cancer risks.

Background: Gastric cancer is a leading cause of cancer morbidity and mortality. Developing information systems which integrate clinical and genomic data may accelerate discoveries to improve cancer prevention, detection, and treatment. To support translational research in gastric cancer, we developed the Gastric Cancer Registry (GCR), a North American repository of clinical and cancer genomics data. Methods: Participants self-enrolled online. Entry criteria into the GCR included the following: (i) diagnosis of gastric cancer, (ii) history of gastric cancer in a first- or second-degree relative, or (iii) known germline mutation in the gene CDH1. Participants provided demographic and clinical information through a detailed survey. Some participants provided specimens of saliva and tumor samples. Tumor samples underwent exome sequencing, whole-genome sequencing, and transcriptome sequencing. Results: From 2011 to 2021, 567 individuals registered and returned the clinical questionnaire. For this cohort 65% had a personal history of gastric cancer, 36% reported a family history of gastric cancer, and 14% had a germline CDH1 mutation. 89 patients with gastric cancer provided tumor samples. For the initial study, 41 tumors were sequenced using next-generation sequencing. The data was analyzed for cancer mutations, copy-number variations, gene expression, microbiome, neoantigens, immune infiltrates, and other features. We developed a searchable, web-based interface (the GCR Genome Explorer) to enable researchers’ access to these datasets. Conclusions: The GCR is a unique, North American gastric cancer registry which integrates clinical and genomic annotation. Impact: Available for researchers through an open access, web-based explorer, the GCR Genome Explorer will accelerate collaborative gastric cancer research across the United States and world.

To chart cell composition and cell state changes that occur during the transformation of healthy colon to precancerous adenomas to colorectal cancer (CRC), we generated single-cell chromatin accessibility profiles and single-cell transcriptomes from 1,000 to 10,000 cells per sample for 48 polyps, 27 normal tissues and 6 CRCs collected from patients with or without germline APC mutations. A large fraction of polyp and CRC cells exhibit a stem-like phenotype, and we define a continuum of epigenetic and transcriptional changes occurring in these stem-like cells as they progress from homeostasis to CRC. Advanced polyps contain increasing numbers of stem-like cells, regulatory T cells and a subtype of pre-cancer-associated fibroblasts. In the cancerous state, we observe T cell exhaustion, RUNX1-regulated cancer-associated fibroblasts and increasing accessibility associated with HNF4A motifs in epithelia. DNA methylation changes in sporadic CRC are strongly anti-correlated with accessibility changes along this continuum, further identifying regulatory markers for molecular staging of polyps.

Clinicians involved in cancer treatment often utilize somatic tumor sequencing to help tailor chemotherapy and immunotherapy. However, somatic tumor sequencing can also identify patients at risk for germline pathogenic variants causing cancer predisposition syndromes like Lynch syndrome. The extent to which clinicians realize this implication of tumor sequencing is currently unclear. We performed a retrospective chart review of Stanford Health Care patients who had somatic variant(s) in the Lynch syndrome genes or microsatellite instability identified on tumor sequencing to determine the proportion of patients who were referred to genetics. Among 6,556 patients who had tumor testing, 90 (1.37%) had findings compatible with Lynch syndrome. Of the 62 patients who had not already seen genetics, 47/62 (75.8%) were not referred to genetics for germline testing. Additionally, 26/47 (55.3%) of these individuals had a tumor type within the Lynch syndrome spectrum. Of the 10 patients who did elect germline testing after tumor sequencing, 3/10 were positive for Lynch syndrome. Our study highlights the need for specific guidelines to inform clinician referral practices on germline follow-up of somatic tumor testing and demonstrates the importance of continued research on the relationship between somatic tumor variants and germline variants to inform such guidelines.

Functional magnetic resonance imaging (fMRI) scanners are unavoidably loud and uncomfortable experimental tools that are necessary for schizophrenia (SZ) neuroscience research. The validity of fMRI paradigms might be undermined by well-known sensory processing abnormalities in SZ that could exert distinct effects on neural activity in the presence of scanner background sound. Given the ubiquity of resting-state fMRI (rs-fMRI) paradigms in SZ research, elucidating the relationship between neural, hemodynamic, and sensory processing deficits during scanning is necessary to refine the construct validity of the MR neuroimaging environment. We recorded simultaneous electroencephalography (EEG)-fMRI at rest in people with SZ (n = 57) and healthy control participants without a psychiatric diagnosis (n = 46) and identified gamma EEG activity in the same frequency range as the background sounds emitted from our scanner during a resting-state sequence. In participants with SZ, gamma coupling to the hemodynamic signal was reduced in bilateral auditory regions of the superior temporal gyri. Impaired gamma-hemodynamic coupling was associated with sensory gating deficits and worse symptom severity. Fundamental sensory-neural processing deficits in SZ are present at rest when considering scanner background sound as a “stimulus.” This finding may impact the interpretation of rs-fMRI activity in studies of people with SZ. Future neuroimaging research in SZ might consider background sound as a confounding variable, potentially related to fluctuations in neural excitability and arousal.

supplementary table TS1

Over the past decade, multiple trials, including the precision medicine trial National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH, EAY131, NCT02465060) have sought to determine if treating cancer based on specific genomic alterations is effective, irrespective of the cancer histology. Although many therapies are now approved for the treatment of cancers harboring specific genomic alterations, most patients do not respond to therapies targeting a single alteration. Further, when antitumor responses do occur, they are often not durable due to the development of drug resistance. Therefore, there is a great need to identify rational combination therapies that may be more effective. To address this need, the NCI and National Clinical Trials Network have developed NCI-ComboMATCH, the successor to NCI-MATCH. Like the original trial, NCI-ComboMATCH is a signal-seeking study. The goal of ComboMATCH is to overcome drug resistance to single-agent therapy and/or utilize novel synergies to increase efficacy by developing genomically-directed combination therapies, supported by strong preclinical in vivo evidence. Although NCI-MATCH was mainly comprised of multiple single-arm studies, NCI-ComboMATCH tests combination therapy, evaluating both combination of targeted agents as well as combinations of targeted therapy with chemotherapy. Although NCI-MATCH was histology agnostic with selected tumor exclusions, ComboMATCH has histology-specific and histology-agnostic arms. Although NCI-MATCH consisted of single-arm studies, ComboMATCH utilizes single-arm as well as randomized designs. NCI-MATCH had a separate, parallel Pediatric MATCH trial, whereas ComboMATCH will include children within the same trial. We present rationale, scientific principles, study design, and logistics supporting the ComboMATCH study.

Contains fulltext : 291574.pdf (Publisher’s version ) (Open Access) Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Supplementary Figure S1. Frequency of genomic aberrations in the KCL TNBC cohort. Supplementary Figure S2. Conceptual diagrams of Scores of Chromosomal Instability Scarring (SCINS). Supplementary Figure S3. Extent and location of SCINS in TNBC. Supplementary Figure S4. Chromosome-wise distribution of SCINS across four TNBC cohorts. Supplementary Figure S5. SCINS-defined tumour classes identify HORMAD1 to be among the top genes linked with Hi-AiCNA/Hi-CnLOH in PrECOG TNBCs. Supplementary Figure S6. Gene expression signatures and HORMAD1 expression. Supplementary Figure S7. Immunofluorescent localisation of HORMAD1 in cell lines. Supplementary Figure S8. Expression of HORMAD1 in breast cancer cell lines and tumour samples. Supplementary Figure S9. HORMAD1 inhibits activity of the DR-GFP HR reporter. Supplementary Figure S10. Effect of HORMAD1 overexpression and knockdown on cell growth and proliferation. Supplementary Figure S11. HORMAD1 promotes activity of the EJ5 NHEJ reporter. Supplementary Figure S12. Effect of HORMAD1 knockdown on 53BP1 and RAD51 foci in HCC1143. Supplementary Figure S13. BRCA1/2 mutation, platinum sensitivity and genomic scarring or HORMAD1 expression. Supplementary Figure S14. Effect of HORMAD1 knockdown on drug sensitivity in HCC1143. Supplementary Figure S15. ROC analysis of PrECOG TNBCs. Supplementary Figure S16. HORMAD1 expression in unselected and BRCA1/2 wildtype TNBCs.

Supplementary Methods, Figure Legends, Table Legends

Supplementary Table S1. KCL TNBC and breast cell line cohort characteristics. Supplementary Table S2. Categories of genomic segment used as the basis for measuring SCINS. Supplementary Table S3. Genes expressed in a SAM of different SCINS clusters. Supplementary Table S4. Gene expression signatures of genomic instability.

SWEAVE document. R code for SCINS analysis.

Figure S2. Bisulfite sequencing after target enrichment provides highly quantitative methylation data across the genome. A) Average read depth for all samples was 71X, with an estimated bisulfite conversion rate of 98.69% across all samples. B) Increased read depth per CpG provides greater quantitative reliability; we routinely observed over 3 million CpGs with at least 5 reads. C) Kernel density plots of each subgroup within the cohort (Affect Carriers, Affected Noncarriers, Healthy Controls, and Unaffected Carriers) showed little global variation. D) Principle Component Analysis of the most variant CpGs across the cohort (n=7,590) did not separate sample subgroups and was only able to capture 5.615% and 1.677% of the variance in principle components 1 and 2, respectively.

Supplemental Figure 1. Patient inclusion and exclusion criteria. TNBC: triple negative breast cancer; ALC: absolute lymphocyte count; nSES: neighborhood socioeconomic status. Supplemental Figure 2a and 2b. Association between minimum lymphocyte count (as percentage of total white blood cell count and absolute value) and stromal tumor infiltrating lymphocytes (sTILs), N=77. Figure 2a. sTILs were correlated with minimum % lymphocyte (p=0.02). Figure 2b. sTILs did not have a significant correlation with minimum absolute (abs) lymphocytes (p=0.36) Supplemental Figure 3. Comparison between Absolute Lymphocyte Count (ALC) and percent peripheral lymphocytes Supplemental Figure 4. Distribution of Absolute Lymphocyte Count (ALC) measures at baseline, defined as ALC value measured within the first three months of breast cancer diagnosis. Supplemental Figure 5. Distribution of minimum Absolute Lymphocyte Count (ALC) values at any time point Supplemental Figure 6. Distribution of overall minimum Absolute Lymphocyte Count (ALC) over time Supplemental Table 1. Multivariable analysis of predictors of lymphopenia (absolute lymphocyte count [ALC]

Details of the allele frequencies in the tumor specimens of patient 15 who was found to have a somatic reversion mutation of BRCA1 in the residual tumor tissue

Figure S1. Summary of HRD testing in PrECOG and combined cisplatin cohorts; Figure S2. Distribution of HRD scores in PrECOG and combined cisplatin cohorts; Figure S3. Performance of HRD in predicting response in PrECOG and combined cisplatin cohorts; Figure S4. Logistic regression models to predict response in PrECOG and combined cisplatin cohorts; Table S1. Study cohorts for threshold training set; Table S2. Summary statistics of HRD scores in BRCA1/2 deficient samples by tissue in training; Table S3. Patient clinical and demographic data; Table S4. HRD score and association with therapy response in entire cohorts; Table S5. Univariate associations between clinical variables and RCB 0/1 or HR deficiency status; Table S6. Analysis of RCB 0/1 and pCR in combined PrECOG 0105 and Cisplatin Trials cohorts (logistic regression models adjusted for cohort)

Purpose: Tumor-infiltrating lymphocytes (TIL) in pretreatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer–specific mortality (BCM) and overall mortality (OM) in TNBC.Experimental Design: Data on treatments and diagnostic tests from electronic medical records of two health care systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM, and OM. For a subgroup with TIL data available, we explored the relationship between TILs and peripheral lymphocyte counts.Results: A total of 1,463 stage I–III TNBC patients were diagnosed from 2000 to 2014; 1,113 (76%) received neoadjuvant/adjuvant chemotherapy within 1 year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC n = 70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy.Conclusions: Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment. Clin Cancer Res; 24(12); 2851–8. ©2018 AACR.

Supplemental Table S1, Figure S1, and Figure Legends for Figure S2 - S5 Table S1. Number of potential allelic methylation sites identified per sample Figure S1. Flow diagram summarizing the strategy for study cohort selection consisting of high-risk breast cancer family index patients.