Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions.

Cancer-microbe associations have been explored for centuries, but cancer-associated fungi have rarely been examined. Here, we comprehensively characterize the cancer mycobiome within 17,401 patient tissue, blood, and plasma samples across 35 cancer types in four independent cohorts. We report fungal DNA and cells at low abundances across many major human cancers, with differences in community compositions that differ among cancer types, even when accounting for technical background. Fungal histological staining of tissue microarrays supported intratumoral presence and frequent spatial association with cancer cells and macrophages. Comparing intratumoral fungal communities with matched bacteriomes and immunomes revealed co-occurring bi-domain ecologies, often with permissive, rather than competitive, microenvironments and distinct immune responses. Clinically focused assessments suggested prognostic and diagnostic capacities of the tissue and plasma mycobiomes, even in stage I cancers, and synergistic predictive performance with bacteriomes.

Divergence of mutational signatures in association with breast cancer subtype.

Abnormal molecular processes occurring throughout the genome leave distinct somatic mutational patterns termed mutational signatures. Exploring the associations between mutational signatures and clinicopathological features can unravel potential mechanisms driving tumorigenic processes. We analyzed whole genome sequencing (WGS) data of tumor and peripheral blood samples from 37 primary breast cancer (BC) patients receiving neoadjuvant chemotherapy. Comprehensive clinico-pathologic features were correlated with genomic profiles and mutational signatures. Somatic mutational landscapes were highly concordant with known BC data sets. Remarkably, we observed a divergence of dominant mutational signatures in association with BC subtype. Signature 5 was overrepresented in hormone receptor positive (HR+) patients, whereas triple-negative tumors mostly lacked Signature 5, but expectedly overrepresented Signature 3. We validated these findings in a large WGS data set of BC, demonstrating dominance of Signature 5 in HR+ patients, mostly in luminal A subtype. We further investigated the association between Signature 5 and gene expression signatures, and identified potential networks, likely related to estrogen regulation. Our results suggest that the yet elusive Signature 5 represents an alternative mechanism for mutation accumulation in HR+ BC, independent of the homologous recombination repair machinery related to Signature 3. This study provides theoretical basis for further elucidating the processes promoting hormonal breast carcinogenesis.

Proteomic patterns associated with response to breast cancer neoadjuvant treatment.

Tumor relapse as a consequence of chemotherapy resistance is a major clinical challenge in advanced stage breast tumors. To identify processes associated with poor clinical outcome, we took a mass spectrometry-based proteomic approach and analyzed a breast cancer cohort of 113 formalin-fixed paraffin-embedded samples. Proteomic profiling of matched tumors before and after chemotherapy, and tumor-adjacent normal tissue, all from the same patients, allowed us to define eight patterns of protein level changes, two of which correlate to better chemotherapy response. Supervised analysis identified two proteins of proline biosynthesis pathway, PYCR1 and ALDH18A1, that were significantly associated with resistance to treatment based on pattern dominance. Weighted gene correlation network analysis of post-treatment samples revealed that these proteins are associated with tumor relapse and affect patient survival. Functional analysis showed that knockdown of PYCR1 reduced invasion and migration capabilities of breast cancer cell lines. PYCR1 knockout significantly reduced tumor burden and increased drug sensitivity of orthotopically injected ER-positive tumor in vivo, thus emphasizing the role of PYCR1 in resistance to chemotherapy.

mRNA-seq whole transcriptome profiling of fresh frozen versus archived fixed tissues.

BACKGROUND: The main bottleneck for genomic studies of tumors is the limited availability of fresh frozen (FF) samples collected from patients, coupled with comprehensive long-term clinical follow-up. This shortage could be alleviated by using existing large archives of routinely obtained and stored Formalin-Fixed Paraffin-Embedded (FFPE) tissues. However, since these samples are partially degraded, their RNA sequencing is technically challenging. RESULTS: In an effort to establish a reliable and practical procedure, we compared three protocols for RNA sequencing using pairs of FF and FFPE samples, both taken from the same breast tumor. In contrast to previous studies, we compared the expression profiles obtained from the two matched sample types, using the same protocol for both. Three protocols were tested on low initial amounts of RNA, as little as 100 ng, to represent the possibly limited availability of clinical samples. For two of the three protocols tested, poly(A) selection (mRNA-seq) and ribosomal-depletion, the total gene expression profiles of matched FF and FFPE pairs were highly correlated. For both protocols, differential gene expression between two FFPE samples was in agreement with their matched FF samples. Notably, although expression levels of FFPE samples by mRNA-seq were mainly represented by the 3'-end of the transcript, they yielded very similar results to those obtained by ribosomal-depletion protocol, which produces uniform coverage across the transcript. Further, focusing on clinically relevant genes, we showed that the high correlation between expression levels persists at higher resolutions. CONCLUSIONS: Using the poly(A) protocol for FFPE exhibited, unexpectedly, similar efficiency to the ribosomal-depletion protocol, with the latter requiring much higher (2-3 fold) sequencing depth to compensate for the relative low fraction of reads mapped to the transcriptome. The results indicate that standard poly(A)-based RNA sequencing of archived FFPE samples is a reliable and cost-effective alternative for measuring mRNA-seq on FF samples. Expression profiling of FFPE samples by mRNA-seq can facilitate much needed extensive retrospective clinical genomic studies.

Aldolase positively regulates of the canonical Wnt signaling pathway.

The Wnt signaling pathway is an evolutionary conserved system, having pivotal roles during animal development. When over-activated, this signaling pathway is involved in cancer initiation and progression. The canonical Wnt pathway regulates the stability of ß-catenin primarily by a destruction complex containing a number of different proteins, including Glycogen synthase kinase 3ß (GSK-3ß) and Axin, that promote proteasomal degradation of ß-catenin. As this signaling cascade is modified by various proteins, novel screens aimed at identifying new Wnt signaling regulators were conducted in our laboratory. One of the different genes that were identified as Wnt signaling activators was Aldolase C (ALDOC). Here we report that ALDOC, Aldolase A (ALDOA) and Aldolase B (ALDOB) activate Wnt signaling in a GSK-3ß-dependent mechanism, by disrupting the GSK-3ß-Axin interaction and targeting Axin to the dishevelled (Dvl)-induced signalosomes that positively regulate the Wnt pathway thus placing the Aldolase proteins as novel Wnt signaling regulators.

Predicting brain metastasis in early stage non-small cell lung cancer patients by gene expression profiling.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the most common cause of cancer-death due to early metastatic spread, in many cases primarily to the brain. Organ-specific pattern of spread of disease might be driven by the activity of a specific signaling pathway within the primary tumors. We aimed to identify an expression signature of genes and the relevant signaling associated with the development of brain metastasis (BM) after surgical resection of NSCLC. METHODS: Rapidly frozen NSCLC surgical specimens were procured from tumor banks. RNA was extracted and analyzed by RNA-sequencing (Illumina HiSeq 2500). Clinical parameters and gene expression were examined for differentiating between patients with BM, patients with metastases to sites other than brain, and patients who did not develop metastatic disease at a clinically significant follow up. Principal component analysis and pathway enrichments studies were done. RESULTS: A total of 91 patients were included in this study, 32 of which developed BM. Stage of disease at diagnosis (P=0.004) and level of differentiation (P=0.007) were significantly different between BM and control group. We identified a set of 22 genes which correlated specifically with BM, and not with metastasis to other sites. This set achieved 93.4% accuracy (95% CI: 86.2-97.5%), 96.6% specificity and 87.5% sensitivity of correctly identifying BM patients in a leave-one-out internal validation analysis. The oxidative phosphorylation pathway was strongly correlated with BM risk. CONCLUSIONS: Expression level of a small set of genes from primary tumors was found to predict BM development, distinctly from metastasis to other organs. These genes and the correlated oxidative phosphorylation pathway require further validation as potentially clinically useful predictors of BM and possibly as novel therapeutic targets for BM prevention.

Stromal-MDM2 Promotes Lung Cancer Cell Invasion through Tumor-Host Feedback Signaling.

Tumor-host interactions play a major role in malignancies' initiation and progression. We have reported in the past that tumor cells attenuate genotoxic stress-induced p53 activation in neighboring stromal cells. Herein, we aim to further elucidate cancer cells' impact on signaling within lung cancer stroma. Primary cancer-associated fibroblasts were grown from resected human lung tumors. Lung cancer lines as well as fresh cultures of resected human lung cancers were used to produce conditioned medium (CM) or cocultured with stromal cells. Invasiveness of cancer cells was evaluated by transwell assays, and in vivo tumor growth was tested in Athymic nude mice. We found CM of a large variety of cancer cell lines as well as ex vivo-cultured lung cancers to rapidly induce protein levels of stromal-MDM2. CM of nontransformed cells had no such effect. Mdm2 induction occurred through enhanced translation, was mTORC1-dependent, and correlated with activation of AKT and p70 S6 Kinase. AKT or MDM2 knockdown in fibroblasts reduced the invasion of neighboring cancer cells, independently of stromal-p53. MDM2 overexpression in fibroblasts enhanced cancer cells' invasion and growth of inoculated tumors in mice. Our results indicate that stromal-MDM2 participates in a p53-independent cancer-host feedback mechanism. Soluble cancer-originated signals induce enhanced translation of stromal-MDM2 through AKT/mTORC1 signaling, which in turn enhances the neighboring cancer cells' invasion ability. The role of these tumor-host interactions needs to be further explored. IMPLICATIONS: We uncovered a novel tumor-stroma signaling loop, which is a potentially new therapeutic target in lung cancer and possibly in additional types of cancer.

The human tumor microbiome is composed of tumor type-specific intracellular bacteria.

Bacteria were first detected in human tumors more than 100 years ago, but the characterization of the tumor microbiome has remained challenging because of its low biomass. We undertook a comprehensive analysis of the tumor microbiome, studying 1526 tumors and their adjacent normal tissues across seven cancer types, including breast, lung, ovary, pancreas, melanoma, bone, and brain tumors. We found that each tumor type has a distinct microbiome composition and that breast cancer has a particularly rich and diverse microbiome. The intratumor bacteria are mostly intracellular and are present in both cancer and immune cells. We also noted correlations between intratumor bacteria or their predicted functions with tumor types and subtypes, patients' smoking status, and the response to immunotherapy.

Tumor Evolution Inferred by Patterns of microRNA Expression through the Course of Disease, Therapy, and Recurrence in Breast Cancer.

PURPOSE: Molecular evolution of tumors during progression, therapy, and metastasis is a major clinical challenge and the main reason for resistance to therapy. We hypothesized that microRNAs (miRNAs) that exhibit similar variation of expression through the course of disease in several patients have a significant function in the tumorigenic process. EXPERIMENTAL DESIGN: Exploration of evolving disease by profiling 800 miRNA expression from serial samples of individual breast cancer patients at several time points: pretreatment, posttreatment, lymph nodes, and recurrence sites when available (58 unique samples from 19 patients). Using a dynamic approach for analysis, we identified expression modulation patterns and classified varying miRNAs into one of the eight possible temporal expression patterns. RESULTS: The various patterns were found to be associated with different tumorigenic pathways. The dominant pattern identified an miRNA set that significantly differentiated between disease stages, and its pattern in each patient was also associated with response to therapy. These miRNAs were related to tumor proliferation and to the cell-cycle pathway, and their mRNA targets showed anticorrelated expression. Interestingly, the level of these miRNAs was lowest in matched recurrent samples from distant metastasis, indicating a gradual increase in proliferative potential through the course of disease. Finally, the average expression level of these miRNAs in the pretreatment biopsy was significantly different comparing patients experiencing recurrence to recurrence-free patients. CONCLUSIONS: Serial tumor sampling combined with analysis of temporal expression patterns enabled to pinpoint significant signatures characterizing breast cancer progression, associated with response to therapy and with risk of recurrence. Clin Cancer Res; 22(14); 3651-62. ©2016 AACR.