An Early Presenting Esophageal Schwannoma

Esophageal schwannoma is a rare diagnosis and historically has been a tumor of middle-aged females. We report a case of a 22-year-old male presenting initially with dyspnea secondary to tracheal compression from an 8 × 6 × 3.0 cm esophageal schwannoma. The tumor was surgically resected, and diagnosis was confirmed with immunohistochemical and pathological studies. We report the youngest case of esophageal schwannoma in an otherwise healthy individual

A primary breast cancer with distinct foci of estrogen receptor-alpha positive and negative cells derived from the same clonal origin as revealed by whole exome sequencing

© 2018, Springer Science+Business Media, LLC, part of Springer Nature. Background/purpose: Tumor heterogeneity is a now well-recognized phenomenon that can affect the classification, prognosis and treatment of human cancers. Heterogeneity is often described in primary breast cancers based upon histologic subtypes, hormone- and HER2-receptor status, and immunolabeling for various markers, which can be seen within a single tumor as mixed cellular populations, or as separate discrete foci. Experimental design/methods: Here, we present a case report of a patient’s primary breast cancer that had two separate but adjacent histologic components, one that was estrogen receptor (ER) positive, and the other ER negative. Each component was subjected to whole exome sequencing and compared for gene identity to determine clonal origin. Results: Using prior bioinformatic tools, we demonstrated that both the ER positive and negative components shared many variants, including passenger and driver alterations. Copy number variations also supported the two components were derived from a single common clone. Conclusions: These analyses strongly suggest that the two ER components of this patient’s breast cancer were derived from the same clonal origin. Our results have implications for the evolution of breast cancers with mixed histologies, and how they might be best managed for optimal therapy

Cytomorphological features of metastatic squamous cell carcinoma in serous effusions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106699/1/cyt12065.pd

BLM Overexpression as a Predictive Biomarker for CHK1 Inhibitor Response in PARP Inhibitor–Resistant BRCA-Mutant Ovarian Cancer

Poly(ADP-ribose) polymerase inhibitors (PARPis) have changed the treatment paradigm in breast cancer gene (BRCA)–mutant high-grade serous ovarian carcinoma (HGSC). However, most patients eventually develop resistance to PARPis, highlighting an unmet need for improved therapeutic strategies. Using high-throughput drug screens, we identified ataxia telangiectasia and rad3-related protein/checkpoint kinase 1 (CHK1) pathway inhibitors as cytotoxic and further validated the activity of the CHK1 inhibitor (CHK1i) prexasertib in PARPi-sensitive and -resistant BRCA-mutant HGSC cells and xenograft mouse models. CHK1i monotherapy induced DNA damage, apoptosis, and tumor size reduction. We then conducted a phase 2 study (NCT02203513) of prexasertib in patients with BRCA-mutant HGSC. The treatment was well tolerated but yielded an objective response rate of 6% (1 of 17; one partial response) in patients with previous PARPi treatment. Exploratory biomarker analyses revealed that replication stress and fork stabilization were associated with clinical benefit to CHK1i. In particular, overexpression of Bloom syndrome RecQ helicase (BLM) and cyclin E1 (CCNE1) overexpression or copy number gain/amplification were seen in patients who derived durable benefit from CHK1i. BRCA reversion mutation in previously PARPi-treated BRCA-mutant patients was not associated with resistance to CHK1i. Our findings suggest that replication fork–related genes should be further evaluated as biomarkers for CHK1i sensitivity in patients with BRCA-mutant HGSC

Immune checkpoint blockade – how does it work in brain metastases?

Immune checkpoints restrain the immune system following its activation and their inhibition unleashes anti-tumor immune responses. Immune checkpoint inhibitors revolutionized the treatment of several cancer types, including melanoma, and immune checkpoint blockade with anti-PD-1 and anti-CTLA-4 antibodies is becoming a frontline therapy in metastatic melanoma. Notably, up to 60% of metastatic melanoma patients develop metastases in the brain. Brain metastases (BrM) are also very common in patients with lung and breast cancer, and occur in ∼20–40% of patients across different cancer types. Metastases in the brain are associated with poor prognosis due to the lack of efficient therapies. In the past, patients with BrM used to be excluded from immune-based clinical trials due to the assumption that such therapies may not work in the context of “immune-specialized” environment in the brain, or may cause harm. However, recent trials in patients with BrM demonstrated safety and intracranial activity of anti-PD-1 and anti-CTLA-4 therapy. We here discuss how immune checkpoint therapy works in BrM, with focus on T cells and the cross-talk between BrM, the immune system, and tumors growing outside the brain. We discuss major open questions in our understanding of what is required for an effective immune checkpoint inhibitor therapy in BrM

Phase II trial correlating standardized uptake value with pathologic complete response to pertuzumab and trastuzumab in breast cancer

PURPOSE Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake values corrected for lean body mass (SULmax) on [ 18 F] fluorodeoxyglucose positron emission tomography/computed tomography would predict pathologic complete response (pCR) to neoadjuvant pertuzumab and trastuzumab (PT). PATIENTS AND METHODS Patients with stage II/III, estrogen receptor–negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. [ 18 F]Fluorodeoxyglucose positron emission tomography/computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percentage of change in SULmax by C1D15 predicting pCR is less than or equal to 0.65, with a one-sided type I error rate of 10%. RESULTS Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 34%. Receiver operating characteristic analysis yielded an area under the curve of 0.76 (90% CI, 0.67 to 0.85), which rejected the null hypothesis. Between patients who obtained pCR versus not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 33.5%; P, .001), an SULmax reduction greater than or equal to 40% was more prevalent (86% v 46%; P, .001; negative predictive value, 88%; positive predictive value, 49%), and a significant difference in median C1D15 SULmax (1.6 v 3.9; P, .001) and higher proportion of C1D15 SULmax less than or equal to 3 (93% v 38%; P, .001; negative predictive value, 94%; positive predictive value, 55%) were observed. CONCLUSION Early changes in SULmax predict response to four cycles of PT in estrogen receptor–negative, HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate a more tailored approach to therapy in this setting

Updated Results of TBCRC026: Phase II Trial Correlating Standardized Uptake Value With Pathological Complete Response to Pertuzumab and Trastuzumab in Breast Cancer

PURPOSE: Predictive biomarkers to identify patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer who may benefit from targeted therapy alone are required. We hypothesized that early measurements of tumor maximum standardized uptake value corrected for lean body mass (SULmax) on 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT) would predict pathologic complete response (pCR) to pertuzumab and trastuzumab (PT). PATIENTS AND METHODS: Patients with stage II or III, estrogen receptor-negative, HER2-positive breast cancer received four cycles of neoadjuvant PT. 18F-labeled fluorodeoxyglucose positron emission tomography-computed tomography was performed at baseline and 15 days after PT initiation (C1D15). Eighty evaluable patients were required to test the null hypothesis that the area under the curve of percent change in SULmax by C1D15 predicting pCR is ≤ 0.65, with a one-sided type I error rate of 10%. RESULTS: Eighty-eight women were enrolled (83 evaluable), and 85% (75 of 88) completed all four cycles of PT. pCR after PT alone was 22%. Receiver operator characteristic analysis of percent change in SULmax by C1D15 yielded an area under the curve of 0.72 (80% CI, 0.64 to 0.80; one-sided P = .12), which did not reject the null hypothesis. However, between patients who obtained pCR and who did not, a significant difference in median percent reduction in SULmax by C1D15 was observed (63.8% v 41.8%; P = .004) and SULmax reduction ≥ 40% was more prevalent (83% v 52%; P = .03; positive predictive value, 31%). Participants not obtaining a 40% reduction in SULmax by C1D15 were unlikely to obtain pCR (negative predictive value, 91%). CONCLUSION: Although the primary objective was not met, early changes in SULmax predict response to PT in estrogen receptor-negative and HER2-positive breast cancer. Once optimized, this quantitative imaging strategy may facilitate tailoring of therapy in this setting

Regulators of genetic risk of breast cancer identified by integrative network analysis.

Genetic risk for breast cancer is conferred by a combination of multiple variants of small effect. To better understand how risk loci might combine, we examined whether risk-associated genes share regulatory mechanisms. We created a breast cancer gene regulatory network comprising transcription factors and groups of putative target genes (regulons) and asked whether specific regulons are enriched for genes associated with risk loci via expression quantitative trait loci (eQTLs). We identified 36 overlapping regulons that were enriched for risk loci and formed a distinct cluster within the network, suggesting shared biology. The risk transcription factors driving these regulons are frequently mutated in cancer and lie in two opposing subgroups, which relate to estrogen receptor (ER)(+) luminal A or luminal B and ER(-) basal-like cancers and to different luminal epithelial cell populations in the adult mammary gland. Our network approach provides a foundation for determining the regulatory circuits governing breast cancer, to identify targets for intervention, and is transferable to other disease settings.This work was funded by Cancer Research UK and the Breast Cancer Research Foundation. MAAC is funded by the National Research Council (CNPq) of Brazil. TEH held a fellowship from the US DOD Breast Cancer Research Program (W81XWH-11-1-0592) and is currently supported by an RAH Career Development Fellowship (Australia). TEH and WDT are funded by the NHMRC of Australia (NHMRC) (ID: 1008349 WDT; 1084416 WDT, TEH) and Cancer Australia/National Breast Cancer Foundation (ID 627229; WDT, TEH). BAJP is a Gibb Fellow of Cancer Research UK. We would like to acknowledge the support of The University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/ng.345