Preoperative profiles of plasma amino acids and derivatives distinguish periampullary cancer and benign disease.

Periampullary cancers, including pancreatic ductal adenocarcinoma, ampullary-, cholangio-, and duodenal carcinoma, are frequently diagnosed in an advanced stage and are associated with poor overall survival. They are difficult to differentiate from each other and challenging to distinguish from benign periampullary disease preoperatively. To improve the preoperative diagnostics of periampullary neoplasms, clinical or biological markers are warranted.In this study, 28 blood plasma amino acids and derivatives from preoperative patients with benign (N = 45) and malignant (N = 72) periampullary disease were analyzed by LC-MS/MS.Principal component analysis and consensus clustering both separated the patients with cancer and the patients with benign disease. Glutamic acid had significantly higher plasma expression and 15 other metabolites significantly lower plasma expression in patients with malignant disease compared with patients having benign disease. Phenylalanine was the only metabolite associated with improved overall survival (HR = 0.50, CI 0.30-0.83, P < 0.01).Taken together, plasma metabolite profiles from patients with malignant and benign periampullary disease were significantly different and have the potential to distinguish malignant from benign disease preoperatively.

Ipilimumab and nivolumab combined with anthracycline-based chemotherapy in metastatic hormone receptor-positive breast cancer: a randomized phase 2b trial.

BACKGROUND: Immune checkpoint inhibitors have shown minimal clinical activity in hormone receptor-positive metastatic breast cancer (HR+mBC). Doxorubicin and low-dose cyclophosphamide are reported to induce immune responses and counter regulatory T cells (Tregs). Here, we report the efficacy and safety of combined programmed cell death protein-1/cytotoxic T-lymphocyte-associated protein 4 blockade concomitant with or after immunomodulatory chemotherapy for HR+mBC. METHODS: Patients with HR+mBC starting first-/second- line chemotherapy (chemo) were randomized 2:3 to chemotherapy (pegylated liposomal doxorubicin 20 mg/m2 every second week plus cyclophosphamide 50 mg by mouth/day in every other 2-week cycle) with or without concomitant ipilimumab (ipi; 1 mg/kg every sixth week) and nivolumab (nivo; 240 mg every second week). Patients in the chemo-only arm were offered cross-over to ipi/nivo without chemotherapy. Co-primary endpoints were safety in all patients starting therapy and progression-free survival (PFS) in the per-protocol (PP) population, defined as all patients evaluated for response and receiving at least two treatment cycles. Secondary endpoints included objective response rate, clinical benefit rate, Treg changes during therapy and assessment of programmed death-ligand 1 (PD-L1), mutational burden and immune gene signatures as biomarkers. RESULTS: Eighty-two patients were randomized and received immune-chemo (N=49) or chemo-only (N=33), 16 patients continued to the ipi/nivo-only cross-over arm. Median follow-up was 41.4 months. Serious adverse events occurred in 63% in the immune-chemo arm, 39% in the chemo-only arm and 31% in the cross-over-arm. In the PP population (N=78) median PFS in the immune-chemo arm was 5.1 months, compared with 3.6 months in the chemo-only arm, with HR 0.94 (95% CI 0.59 to 1.51). Clinical benefit rates were 55% (26/47) and 48% (15/31) in the immune-chemo and chemo-only arms, respectively. In the cross-over-arm (ipi/nivo-only), objective responses were observed in 19% of patients (3/16) and clinical benefit in 25% (4/16). Treg levels in blood decreased after study chemotherapy. High-grade immune-related adverse events were associated with prolonged PFS. PD-L1 status and mutational burden were not associated with ipi/nivo benefit, whereas a numerical PFS advantage was observed for patients with a high Treg gene signature in tumor. CONCLUSION: The addition of ipi/nivo to chemotherapy increased toxicity without improving efficacy. Ipi/nivo administered sequentially to chemotherapy was tolerable and induced clinical responses. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov Identifier: NCT03409198.

Transcriptomic subtyping of malignant peripheral nerve sheath tumours highlights immune signatures, genomic profiles, patient survival and therapeutic targets.

BACKGROUND: Malignant peripheral nerve sheath tumour (MPNST) is an aggressive orphan disease commonly affecting adolescents or young adults. Current knowledge of molecular tumour biology has been insufficient for development of rational treatment strategies. We aimed to discover molecular subtypes of potential clinical relevance. METHODS: Fresh frozen samples of MPNSTs (n = 94) and benign neurofibromas (n = 28) from 115 patients in a European multicentre study were analysed by DNA copy number and/or transcriptomic profiling. Unsupervised transcriptomic subtyping was performed and the subtypes characterized for genomic aberrations, clinicopathological associations and patient survival. FINDINGS: MPNSTs were classified into two transcriptomic subtypes defined primarily by immune signatures and proliferative processes. "Immune active" MPNSTs (44%) had sustained immune signals relative to neurofibromas, were more frequently low-grade (P = 0.01) and had favourable prognostic associations in a multivariable model of disease-specific survival with clinicopathological factors (hazard ratio 0.25, P = 0.003). "Immune deficient" MPNSTs were more aggressive and characterized by proliferative signatures, high genomic complexity, aberrant TP53 and PRC2 loss, as well as high relative expression of several potential actionable targets (EGFR, ERBB2, EZH2, KIF11, PLK1, RRM2). Integrated gene-wise analyses suggested a DNA copy number-basis for proliferative transcriptomic signatures in particular, and the tumour copy number burden further stratified the transcriptomic subtypes according to patient prognosis (P < 0.01). INTERPRETATION: Approximately half of MPNSTs belong to an "immune deficient" transcriptomic subtype associated with an aggressive disease course, PRC2 loss and expression of several potential therapeutic targets, providing a rationale for molecularly-guided intervention trials. FUNDING: Research grants from non-profit organizations, as stated in the Acknowledgements.

Gene expression and copy number profiling of follicular lymphoma biopsies from patients treated with first-line rituximab without chemotherapy.

The Nordic Lymphoma Study Group has performed two randomized clinical trials with chemotherapy-free first-line treatment (rituximab +/- interferon) in follicular lymphoma (FL), with 73% of patients alive and 38% without any need of chemotherapy after 10.6 years median follow-up. In order to identify predictive markers, that may also serve as therapeutic targets, gene expression- and copy number profiles were obtained from 97 FL patients using whole genome microarrays. Copy number alterations (CNAs) were identified, e.g. by GISTIC. Cox Lasso Regression and Lasso logistic regression were used to determine molecular features predictive of time to next therapy (TTNT). A few molecular changes were associated with TTNT (e.g. increased expression of INPP5B, gains in 12q23/q24), but were not significant after adjusting for multiple testing. Our findings suggest that there are no strong determinants of patient outcome with respect to GE data and CNAs in FL patients treated with a chemotherapy-free regimen (i.e. rituximab +/- interferon).

Cis-regulatory mutations associate with transcriptional and post-transcriptional deregulation of gene regulatory programs in cancers.

Most cancer alterations occur in the noncoding portion of the human genome, where regulatory regions control gene expression. The discovery of noncoding mutations altering the cells' regulatory programs has been limited to few examples with high recurrence or high functional impact. Here, we show that transcription factor binding sites (TFBSs) have similar mutation loads to those in protein-coding exons. By combining cancer somatic mutations in TFBSs and expression data for protein-coding and miRNA genes, we evaluate the combined effects of transcriptional and post-transcriptional alterations on the regulatory programs in cancers. The analysis of seven TCGA cohorts culminates with the identification of protein-coding and miRNA genes linked to mutations at TFBSs that are associated with a cascading trans-effect deregulation on the cells' regulatory programs. Our analyses of cis-regulatory mutations associated with miRNAs recurrently predict 12 mature miRNAs (derived from 7 precursors) associated with the deregulation of their target gene networks. The predictions are enriched for cancer-associated protein-coding and miRNA genes and highlight cis-regulatory mutations associated with the dysregulation of key pathways associated with carcinogenesis. By combining transcriptional and post-transcriptional regulation of gene expression, our method predicts cis-regulatory mutations related to the dysregulation of key gene regulatory networks in cancer patients.

Prognostic Significance of the Loss of Heterozygosity of KRAS in Early-Stage Lung Adenocarcinoma.

Lung cancer is a common disease with a poor prognosis. Genomic alterations involving the KRAS gene are common in lung carcinomas, although much is unknown about how different mutations, deletions, and expressions influence the disease course. The first approval of a KRAS-directed inhibitor was recently approved by the FDA. Mutations in the KRAS gene have been associated with poor prognosis for lung adenocarcinomas, but implications of the loss of heterozygosity (LOH) of KRAS have not been investigated. In this study, we have assessed the LOH of KRAS in early-stage lung adenocarcinoma by analyzing DNA copy number profiles and have investigated the effect on patient outcome in association with mRNA expression and somatic hotspot mutations. KRAS mutation was present in 36% of cases and was associated with elevated mRNA expression. LOH in KRAS was associated with a favorable prognosis, more prominently in KRAS mutated than in wild-type patients. The presence of both LOH and mutation in KRAS conferred a better prognosis than KRAS mutation alone. For wild-type tumors, no difference in prognosis was observed between patients with and without LOH in KRAS. Our study indicates that LOH in KRAS is an independent prognostic factor that may refine the existing prognostic groups of lung adenocarcinomas.

NRF2 drives an oxidative stress response predictive of breast cancer.

Many breast cancer patients are diagnosed with small, well-differentiated, hormone receptor-positive tumors. Risk of relapse is not easily identified in these patients, resulting in overtreatment. To identify metastasis-related gene expression patterns, we compared the transcriptomes of the non-metastatic 67NR and metastatic 66cl4 cell lines from the murine 4T1 mammary tumor model. The transcription factor nuclear factor, erythroid 2-like 2 (NRF2, encoded by NFE2L2) was constitutively activated in the metastatic cells and tumors, and correspondingly a subset of established NRF2-regulated genes was also upregulated. Depletion of NRF2 increased basal levels of reactive oxygen species (ROS) and severely reduced ability to form primary tumors and lung metastases. Consistently, a set of NRF2-controlled genes was elevated in breast cancer biopsies. Sixteen of these were combined into a gene expression signature that significantly improves the PAM50 ROR score, and is an independent, strong predictor of prognosis, even in hormone receptor-positive tumors.

Proteome Analysis of Pancreatic Tumors Implicates Extracellular Matrix in Patient Outcome.

Pancreatic cancer remains a disease with unmet clinical needs and inadequate diagnostic, prognostic, and predictive biomarkers. In-depth characterization of the disease proteome is limited. This study thus aims to define and describe protein networks underlying pancreatic cancer and identify protein centric subtypes with clinical relevance. Mass spectrometry-based proteomics was used to identify and quantify the proteome in tumor tissue, tumor-adjacent tissue, and patient-derived xenografts (PDX)-derived cell lines from patients with pancreatic cancer, and tissues from patients with chronic pancreatitis. We identified, quantified, and characterized 11,634 proteins from 72 pancreatic tissue samples. Network focused analysis of the proteomics data led to identification of a tumor epithelium-specific module and an extracellular matrix (ECM)-associated module that discriminated pancreatic tumor tissue from both tumor adjacent tissue and pancreatitis tissue. On the basis of the ECM module, we defined an ECM-high and an ECM-low subgroup, where the ECM-high subgroup was associated with poor prognosis (median survival months: 15.3 vs. 22.9 months; log-rank test, P = 0.02). The ECM-high tumors were characterized by elevated epithelial-mesenchymal transition and glycolytic activities, and low oxidative phosphorylation, E2F, and DNA repair pathway activities. This study offers novel insights into the protein network underlying pancreatic cancer opening up for proteome precision medicine development. Significance: Pancreatic cancer lacks reliable biomarkers for prognostication and treatment of patients. We analyzed the proteome of pancreatic tumors, nonmalignant tissues of the pancreas and PDX-derived cell lines, and identified proteins that discriminate between patients with good and poor survival. The proteomics data also unraveled potential novel drug targets.

Breast cancer metastasis: immune profiling of lymph nodes reveals exhaustion of effector T cells and immunosuppression.

Sentinel lymph nodes are the first nodes draining the lymph from a breast and could reveal early changes in the host immune system upon dissemination of breast cancer cells. To investigate this, we performed single-cell immune profiling of lymph nodes with and without metastatic cells. Whereas no significant changes were observed for B-cell and natural killer (NK)-cell subsets, metastatic lymph nodes had a significantly increased frequency of CD8 T cells and a skewing toward an effector/memory phenotype of CD4 and CD8 T cells, suggesting an ongoing immune response. Additionally, metastatic lymph nodes had an increased frequency of TIGIT (T-cell immunoreceptor with Ig and ITIM domains)-positive T cells with suppressed TCR signaling compared with non-metastatic nodes, indicating exhaustion of effector T cells, and an increased frequency of regulatory T cells (Tregs) with an activated phenotype. T-cell alterations correlated with the percentage of metastatic tumor cells, reflecting the presence of metastatic tumor cells driving T effector cells toward exhaustion and promoting immunosuppression by recruitment or increased differentiation toward Tregs. These results show that immune suppression occurs already in early stages of tumor progression.

Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer.

The PAM50 gene expression subtypes and the associated risk of recurrence (ROR) score are used to predict the risk of recurrence and the benefits of adjuvant therapy in early-stage breast cancer. The Prosigna assay includes the PAM50 subtypes along with their clinicopathological features, and is approved for treatment recommendations for adjuvant hormonal therapy and chemotherapy in hormone-receptor-positive early breast cancer. The Prosigna test utilizes RNA extracted from macrodissected tumor cells obtained from formalin-fixed, paraffin-embedded (FFPE) tissue sections. However, RNA extracted from fresh-frozen (FF) bulk tissue without macrodissection is widely used for research purposes, and yields high-quality RNA for downstream analyses. To investigate the impact of the sample preparation approach on ROR scores, we analyzed 94 breast carcinomas included in an observational study that had available gene expression data from macrodissected FFPE tissue and FF bulk tumor tissue, along with the clinically approved Prosigna scores for the node-negative, hormone-receptor-positive, HER2-negative cases (n = 54). ROR scores were calculated in R; the resulting two sets of scores from FFPE and FF samples were compared, and treatment recommendations were evaluated. Overall, ROR scores calculated based on the macrodissected FFPE tissue were consistent with the Prosigna scores. However, analyses from bulk tissue yielded a higher proportion of cases classified as normal-like; these were samples with relatively low tumor cellularity, leading to lower ROR scores. When comparing ROR scores (low, intermediate, and high), discordant cases between the two preparation approaches were revealed among the luminal tumors; the recommended treatment would have changed in a minority of cases.

Whole genome copy number analyses reveal a highly aberrant genome in TP53 mutant lung adenocarcinoma tumors.

BACKGROUND: Genetic alterations are common in non-small cell lung cancer (NSCLC), and DNA mutations and translocations are targets for therapy. Copy number aberrations occur frequently in NSCLC tumors and may influence gene expression and further alter signaling pathways. In this study we aimed to characterize the genomic architecture of NSCLC tumors and to identify genomic differences between tumors stratified by histology and mutation status. Furthermore, we sought to integrate DNA copy number data with mRNA expression to find genes with expression putatively regulated by copy number aberrations and the oncogenic pathways associated with these affected genes. METHODS: Copy number data were obtained from 190 resected early-stage NSCLC tumors and gene expression data were available from 113 of the adenocarcinomas. Clinical and histopathological data were known, and EGFR-, KRAS- and TP53 mutation status was determined. Allele-specific copy number profiles were calculated using ASCAT, and regional copy number aberration were subsequently obtained and analyzed jointly with the gene expression data. RESULTS: The NSCLC tumors tissue displayed overall complex DNA copy number profiles with numerous recurrent aberrations. Despite histological differences, tissue samples from squamous cell carcinomas and adenocarcinomas had remarkably similar copy number patterns. The TP53-mutated lung adenocarcinomas displayed a highly aberrant genome, with significantly altered copy number profiles including gains, losses and focal complex events. The EGFR-mutant lung adenocarcinomas had specific arm-wise aberrations particularly at chromosome7p and 9q. A large number of genes displayed correlation between copy number and expression level, and the PI(3)K-mTOR pathway was highly enriched for such genes. CONCLUSIONS: The genomic architecture in NSCLC tumors is complex, and particularly TP53-mutated lung adenocarcinomas displayed highly aberrant copy number profiles. We suggest to always include TP53-mutation status when studying copy number aberrations in NSCLC tumors. Copy number may further impact gene expression and alter cellular signaling pathways.

Protein Signature Predicts Response to Neoadjuvant Treatment With Chemotherapy and Bevacizumab in HER2-Negative Breast Cancers.

PURPOSE: Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS: In the NeoAva phase II clinical trial, patients (N = 132) with large (≥ 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS: We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P < .001) and in patients with low RCB (P < .001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). CONCLUSION: Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.

Clinicopathological factors associated with tumour-specific mutation detection in plasma of patients with RAS-mutated or BRAF-mutated metastatic colorectal cancer.

Detection of tumour-specific circulating cell-free DNA in plasma (ctDNA) fails in a significant number of cases depending on the clinical context. The primary aim was to investigate clinicopathological factors associated with detection of ctDNA in patients with RAS-/BRAF-mutated metastatic colorectal cancer (mCRC) prior to first-line therapy. A secondary aim was to evaluate the prognostic impact of ctDNA compared to other biomarkers. Patients were included from the NORDIC-VII study (N = 253). ctDNA was sampled prior to treatment and analysed for hotspot tissue mutations (KRAS, NRAS, and BRAF) using droplet digital PCR. Multivariable regression models were constructed to predict the probability of mutation detection and survival. Increasing radiological size of target lesions by increments of 1 cm (odds ratio [OR] = 1.18; 95% confidence interval [CI] 1.09-1.27; P < .001), intact primary tumour (OR = 3.17; 95% CI 1.22-8.22; P = .018) and more than one metastatic site (OR = 3.08; 95% CI 1.32-7.19; P = .009) were associated with mutation detection in plasma. Metastatic involvement of the lung was associated with non-detection (OR = 0.26; 95% CI 0.12-0.58; P = .001). Preanalytical and analytical factors modulated detection. High allele frequencies of ctDNA indicated poor prognosis independently of CEA and CA19-9 (hazard ratio [HR] = 2.38; 95% CI 1.74-3.26; P < .001; N = 206). Clinicopathological characteristics should be carefully considered when evaluating ctDNA results from mCRC patients, especially when confronted with a plasma negative result. ctDNA may prove to be a clinically useful marker in the evaluation of mCRC treatment.

miRNA normalization enables joint analysis of several datasets to increase sensitivity and to reveal novel miRNAs differentially expressed in breast cancer.

Different miRNA profiling protocols and technologies introduce differences in the resulting quantitative expression profiles. These include differences in the presence (and measurability) of certain miRNAs. We present and examine a method based on quantile normalization, Adjusted Quantile Normalization (AQuN), to combine miRNA expression data from multiple studies in breast cancer into a single joint dataset for integrative analysis. By pooling multiple datasets, we obtain increased statistical power, surfacing patterns that do not emerge as statistically significant when separately analyzing these datasets. To merge several datasets, as we do here, one needs to overcome both technical and batch differences between these datasets. We compare several approaches for merging and jointly analyzing miRNA datasets. We investigate the statistical confidence for known results and highlight potential new findings that resulted from the joint analysis using AQuN. In particular, we detect several miRNAs to be differentially expressed in estrogen receptor (ER) positive versus ER negative samples. In addition, we identify new potential biomarkers and therapeutic targets for both clinical groups. As a specific example, using the AQuN-derived dataset we detect hsa-miR-193b-5p to have a statistically significant over-expression in the ER positive group, a phenomenon that was not previously reported. Furthermore, as demonstrated by functional assays in breast cancer cell lines, overexpression of hsa-miR-193b-5p in breast cancer cell lines resulted in decreased cell viability in addition to inducing apoptosis. Together, these observations suggest a novel functional role for this miRNA in breast cancer. Packages implementing AQuN are provided for Python and Matlab: https://github.com/YakhiniGroup/PyAQN.

A Systemic Protein Deviation Score Linked to PD-1+ CD8+ T Cell Expansion That Predicts Overall Survival in Diffuse Large B Cell Lymphoma.

BACKGROUND: Current prognostic variables can only partly explain the large outcome heterogeneity in diffuse large B cell lymphoma (DLBCL). We aimed to investigate the utility of systems-level protein and immune repertoire profiling for outcome prognostication in DLBCL. METHODS: In this retrospective study, we used proximity extension assay technology to quantify 81 immune-related proteins in serum or plasma in 2 independent cohorts in a total 111 DLBCL patients. Protein levels were assessed before and after treatment with rituximab and chemotherapy, and the patients were compared with 19 age- and sex-matched healthy blood donors. In a subset of the patients, we performed a broad mass cytometric characterization of immune cell repertoires in peripheral blood. FINDINGS: Patients displayed large deviations in protein profiles compared with healthy controls. Development of a systemic protein deviation (SPD) score provided a 4-protein-based metric that reflected the overall degree of protein deviations compared with age- and sex-matched healthy blood donors. The SPD score identified patients with very poor overall survival in both cohorts and correlated with increased frequencies of peripheral blood PD-1+ CD8+ T cells, and expansion of myeloid-derived suppressor cells. CONCLUSIONS: Our results show that a simple metric based on measurement of a small set of serum or plasma proteins can be used to probe systemic immune changes associated with poor survival in DLBCL. This finding warrants further investigation in larger, prospective studies to establish a clinical prognostic biomarker.

Immune phenotype of tumor microenvironment predicts response to bevacizumab in neoadjuvant treatment of ER-positive breast cancer.

Antiangiogenic drugs are potentially a useful supplement to neoadjuvant chemotherapy for a subgroup of patients with human epidermal growth factor receptor 2 (HER2) negative breast cancer, but reliable biomarkers for improved response are lacking. Here, we report on a randomized phase II clinical trial to study the added effect of bevacizumab in neoadjuvant chemotherapy with FEC100 (5-fluorouracil, epirubicin and cyclophosphamide) and taxanes (n = 132 patients). Gene expression from the tumors was obtained before neoadjuvant treatment, and treatment response was evaluated by residual cancer burden (RCB) at time of surgery. Bevacizumab increased the proportion of complete responders (RCB class 0) from 5% to 20% among patients with estrogen receptor (ER) positive tumors (P = .02). Treatment with bevacizumab was associated with improved 8-year disease-free survival (P = .03) among the good responders (RCB class 0 or I). Patients treated with paclitaxel (n = 45) responded better than those treated with docetaxel (n = 21; P = .03). Improved treatment response was associated with higher proliferation rate and an immune phenotype characterized by high presence of classically activated M1 macrophages, activated NK cells and memory activated CD4 T cells. Treatment with bevacizumab increased the number of adverse events, including hemorrhage, hypertension, infection and febrile neutropenia, but despite this, the ECOG status was not affected.

DNA copy number motifs are strong and independent predictors of survival in breast cancer.

Somatic copy number alterations are a frequent sign of genome instability in cancer. A precise characterization of the genome architecture would reveal underlying instability mechanisms and provide an instrument for outcome prediction and treatment guidance. Here we show that the local spatial behavior of copy number profiles conveys important information about this architecture. Six filters were defined to characterize regional traits in copy number profiles, and the resulting Copy Aberration Regional Mapping Analysis (CARMA) algorithm was applied to tumors in four breast cancer cohorts (n = 2919). The derived motifs represent a layer of information that complements established molecular classifications of breast cancer. A score reflecting presence or absence of motifs provided a highly significant independent prognostic predictor. Results were consistent between cohorts. The nonsite-specific occurrence of the detected patterns suggests that CARMA captures underlying replication and repair defects and could have a future potential in treatment stratification.

Molecularly matched therapy in the context of sensitivity, resistance, and safety; patient outcomes in end-stage cancer - the MetAction study.

Background: In precision cancer medicine, the challenge is to prioritize DNA driver events, account for resistance markers, and procure sufficient information for treatment that maintains patient safety. The MetAction project, exploring how tumor molecular vulnerabilities predict therapy response, first established the required workflow for DNA sequencing and data interpretation (2014-2015). Here, we employed it to identify molecularly matched therapy and recorded outcome in end-stage cancer (2016-2019).Material and methods: Metastatic tissue from 26 patients (16 colorectal cancer cases) was sequenced by the Oncomine assay. The study tumor boards interpreted called variants with respect to sensitivity or resistance to matched therapy and recommended single-agent or combination treatment if considered tolerable. The primary endpoint was the rate of progression-free survival 1.3-fold longer than for the most recent systemic therapy. The objective response rate and overall survival were secondary endpoints.Results: Both common and rare actionable alterations were identified. Thirteen patients were found eligible for therapy following review of tumor sensitivity and resistance variants and patient tolerability. The interventions were inhibitors of ALK/ROS1-, BRAF-, EGFR-, FGFR-, mTOR-, PARP-, or PD-1-mediated signaling for 2-3 cases each. Among 10 patients who received treatment until radiologic evaluation, 6 (46% of the eligible cases) met the primary endpoint. Four colorectal cancer patients (15% of the total study cohort) had objective response. The only serious adverse event was a transient colitis, which appeared in 1 of the 2 patients given PD-1 inhibitor with complete response. Apart from those two, overall survival was similar for patients who did and did not receive study treatment.Conclusions: The systematic MetAction approach may point forward to a refined framework for how to interpret the complexity of sensitivity versus resistance and patient safety that resides in tumor sequence data, for the possibly improved outcome of precision cancer medicine in future studies. ClinicalTrials.gov, identifier: NCT02142036.

PathTracer: High-sensitivity detection of differential pathway activity in tumours.

Gene expression profiling of tumours is an important source of information for cancer patient stratification. Detecting subtle alterations of gene expression remains a challenge, however. Here, we propose a novel tool for high-sensitivity detection of differential pathway activity in tumours. For a pathway defined by a collection of genes, the samples are projected onto a low-dimensional manifold in the subspace spanned by those genes. For each sample, a score is next found by calculating the distance between each projected sample and the projection of a subgroup of reference samples. Depending on the aim of the analysis and the available data, the reference samples may represent e.g. normal tissue or tumour samples with a particular genotype or phenotype. The proposed tool, PathTracer, is demonstrated on gene expression data from 1952 invasive breast cancer samples, 10 DCIS, 9 benign samples and 144 tumour adjacent normal breast tissue samples. PathTracer scores are shown to predict survival, clinical subtypes, cellular proliferation and genomic instability. Furthermore, predictions are shown to outperform those obtained with other comparable methods.