Caveolin-1 gene expression provides additional prognostic information combined with PAM50 risk of recurrence (ROR) score in breast cancer.

Combining information from the tumor microenvironment (TME) with PAM50 Risk of Recurrence (ROR) score could improve breast cancer prognostication. Caveolin-1 (CAV1) is a marker of an active TME. CAV1 is a membrane protein involved in cell signaling, extracellular matrix organization, and tumor-stroma interactions. We sought to investigate CAV1 gene expression in relation to PAM50 subtypes, ROR score, and their joint prognostic impact. CAV1 expression was compared between PAM50 subtypes and ROR categories in two cohorts (SCAN-B, n = 5326 and METABRIC, n = 1980). CAV1 expression was assessed in relation to clinical outcomes using Cox regression and adjusted for clinicopathological predictors. Effect modifications between CAV1 expression and ROR categories on clinical outcome were investigated using multiplicative and additive two-way interaction analyses. Differential gene expression and gene set enrichment analyses were applied to compare high and low expressing CAV1 tumors. All samples expressed CAV1 with the highest expression in the Normal-like subtype. Gene modules consistent with epithelial-mesenchymal transition (EMT), hypoxia, and stromal activation were associated with high CAV1 expression. CAV1 expression was inversely associated with ROR category. Interactions between CAV1 expression and ROR categories were observed in both cohorts. High expressing CAV1 tumors conferred worse prognosis only within the group classified as ROR high. ROR gave markedly different prognostic information depending on the underlying CAV1 expression. CAV1, a potential mediator between the malignant cells and TME, could be a useful biomarker that enhances and further refines PAM50 ROR risk stratification in patients with ROR high tumors and a potential therapeutic target.

The role of serum thymidine kinase 1 activity in neoadjuvant-treated HER2-positive breast cancer: biomarker analysis from the Swedish phase II randomized PREDIX HER2 trial.

BACKGROUND: Thymidine kinase 1 (TK1) plays a pivotal role in DNA synthesis and cellular proliferation. TK1 has been studied as a prognostic marker and as an early indicator of treatment response in human epidermal growth factor 2 (HER2)-negative early and metastatic breast cancer (BC). However, the prognostic and predictive value of serial TK1 activity in HER2-positive BC remains unknown. METHODS: In the PREDIX HER2 trial, 197 HER2-positive BC patients were randomized to neoadjuvant trastuzumab, pertuzumab, and docetaxel (DPH) or trastuzumab emtansine (T-DM1), followed by surgery and adjuvant epirubicin and cyclophosphamide. Serum samples were prospectively collected from all participants at multiple timepoints: at baseline, after cycle 1, 2, 4, and 6, at end of adjuvant therapy, annually for a total period of 5 years and/or at the time of recurrence. The associations of sTK1 activity with baseline characteristics, pathologic complete response (pCR), event-free survival (EFS), and disease-free survival (DFS) were evaluated. RESULTS: No association was detected between baseline sTK1 levels and all the baseline clinicopathologic characteristics. An increase of TK1 activity from baseline to cycle 2 was seen in all cases. sTK1 level at baseline, after 2 and 4 cycles was not associated with pCR status. After a median follow-up of 58 months, 23 patients had EFS events. There was no significant effect between baseline or cycle 2 sTK1 activity and time to event. A non-significant trend was noted among patents with residual disease (non-pCR) and high sTK1 activity at the end of treatment visit, indicating a potentially worse long-term prognosis. CONCLUSION: sTK1 activity increased following neoadjuvant therapy for HER2-positive BC but was not associated with patient outcomes or treatment benefit. However, the post-surgery prognostic value in patients that have not attained pCR warrants further investigation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02568839. Registered on 6 October 2015.

Comparison of SP142 and 22C3 PD-L1 assays in a population-based cohort of triple-negative breast cancer patients in the context of their clinically established scoring algorithms.

BACKGROUND: Immunohistochemical (IHC) PD-L1 expression is commonly employed as predictive biomarker for checkpoint inhibitors in triple-negative breast cancer (TNBC). However, IHC evaluation methods are non-uniform and further studies are needed to optimize clinical utility. METHODS: We compared the concordance, prognostic value and gene expression between PD-L1 IHC expression by SP142 immune cell (IC) score and 22C3 combined positive score (CPS; companion IHC diagnostic assays for atezolizumab and pembrolizumab, respectively) in a population-based cohort of 232 early-stage TNBC patients. RESULTS: The expression rates of PD-L1 for SP142 IC ≥ 1%, 22C3 CPS ≥ 10, 22C3 CPS ≥ 1 and 22C3 IC ≥ 1% were 50.9%, 27.2%, 53.9% and 41.8%, respectively. The analytical concordance (kappa values) between SP142 IC+ and these three different 22C3 scorings were 73.7% (0.48, weak agreement), 81.5% (0.63) and 86.6% (0.73), respectively. The SP142 assay was better at identifying 22C3 positive tumors than the 22C3 assay was at detecting SP142 positive tumors. PD-L1 (CD274) gene expression (mRNA) showed a strong positive association with all two-categorical IHC scorings of the PD-L1 expression, irrespective of antibody and cut-off (Spearman Rho ranged from 0.59 to 0.62; all p-values < 0.001). PD-L1 IHC positivity and abundance of tumor infiltrating lymphocytes were of positive prognostic value in univariable regression analyses in patients treated with (neo)adjuvant chemotherapy, where it was strongest for 22C3 CPS ≥ 10 and distant relapse-free interval (HR = 0.18, p = 0.019). However, PD-L1 status was not independently prognostic when adjusting for abundance of tumor infiltrating lymphocytes in multivariable analyses. CONCLUSION: Our findings support that the SP142 and 22C3 IHC assays, with their respective clinically applied scoring algorithms, are not analytically equivalent where they identify partially non-overlapping subpopulations of TNBC patients and cannot be substituted with one another regarding PD-L1 detection. Trial registration The Swedish Cancerome Analysis Network - Breast (SCAN-B) study, retrospectively registered 2nd Dec 2014 at ClinicalTrials.gov; ID NCT02306096.

The Lucerne Toolbox 2 to optimise axillary management for early breast cancer: a multidisciplinary expert consensus.

Clinical axillary lymph node management in early breast cancer has evolved from being merely an aspect of surgical management and now includes the entire multidisciplinary team. The second edition of the "Lucerne Toolbox", a multidisciplinary consortium of European cancer societies and patient representatives, addresses the challenges of clinical axillary lymph node management, from diagnosis to local therapy of the axilla. Five working packages were developed, following the patients' journey and addressing specific clinical scenarios. Panellists voted on 72 statements, reaching consensus (agreement of 75% or more) in 52.8%, majority (51%-74% agreement) in 43.1%, and no decision in 4.2%. Based on the votes, targeted imaging and standardized pathology of lymph nodes should be a prerequisite to planning local and systemic therapy, axillary lymph node dissection can be replaced by sentinel lymph node biopsy ( ± targeted approaches) in a majority of scenarios; and positive patient outcomes should be driven by both low recurrence risks and low rates of lymphoedema.

Caveolin-1 genotypes as predictor for locoregional recurrence and contralateral disease in breast cancer.

PURPOSE: Caveolin-1 (CAV1) has been implicated in breast cancer oncogenesis and metastasis and may be a potential prognosticator, especially for non-distant events. CAV1 functions as a master regulator of membrane transport and cell signaling. Several CAV1 SNPs have been linked to multiple cancers, but the prognostic impact of CAV1 SNPs in breast cancer remains unclear. Here, we investigated CAV1 polymorphisms in relation to clinical outcomes in breast cancer. METHODS: A cohort of 1017 breast cancer patients (inclusion 2002-2012, Sweden) were genotyped using Oncoarray by Ilumina. Patients were followed for up to 15 years. Five out of six CAV1 SNPs (rs10256914, rs959173, rs3807989, rs3815412, and rs8713) passed quality control and were used for haplotype construction. CAV1 genotypes and haplotypes in relation to clinical outcomes were assessed with Cox regression and adjusted for potential confounders (age, tumor characteristics, and adjuvant treatments). RESULTS: Only one SNP was associated with lymph node status, no other SNPs or haplotypes were associated with tumor characteristics. The CAV1 rs3815412 CC genotype (5.8% of patients) was associated with increased risk of contralateral breast cancer, adjusted hazard ratio (HRadj) 4.26 (95% CI 1.86-9.73). Moreover, the TTACA haplotype (13% of patients) conferred an increased risk for locoregional recurrence HRadj 2.24 (95% CI 1.24-4.04). No other genotypes or haplotypes were associated with clinical outcome. CONCLUSION: CAV1 polymorphisms were associated with increased risk for locoregional recurrence and contralateral breast cancer. These findings may identify patients that could derive benefit from more tailored treatment to prevent non-distant events, if confirmed.

Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial.

PURPOSE: PREDIX HER2 is a randomized Phase II trial that compared neoadjuvant docetaxel, trastuzumab, and pertuzumab (THP) with trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Rates of pathologic complete response (pCR) did not differ between the two groups. Here, we present the survival outcomes from PREDIX HER2 and investigate metabolic response and tumor-infiltrating lymphocytes (TIL) as prognostic factors. PATIENTS AND METHODS: In total, 202 patients with HER2-positive breast cancer were enrolled and 197 patients received six cycles of either THP or T-DM1. Secondary endpoints included event-free survival (EFS), recurrence-free survival (RFS), and overall survival (OS). Assessment with PET/CT was performed at baseline, after two and six treatment cycles. TILs were assessed manually at baseline biopsies, while image-based evaluation of TILs [digital TILs (DTIL)] was performed in digitized full-face sections. RESULTS: After a median follow-up of 5.21 years, there was no difference between the two treatment groups in terms of EFS [HR = 1.26; 95% confidence interval (CI), 0.54-2.91], RFS (HR = 0.69; 95% CI, 0.24-1.93), or OS (HR = 0.52; 95% CI, 0.09-2.82). Higher SUVmax at cycle 2 (C2) predicted lower pCR (ORadj = 0.65; 95% CI, 0.48-0.87; P = 0.005) and worse EFS (HRadj = 1.27; 95% CI, 1.12-1.41; P < 0.001). Baseline TILs and DTILs provided additional prognostic information to clinical parameters and C2 SUVmax. CONCLUSIONS: Long-term outcomes following neoadjuvant T-DM1 were similar to neoadjuvant THP. SUVmax after two cycles of neoadjuvant therapy for HER2-positive breast cancer may be an independent predictor of both short- and long-term outcomes. Combined assessment with TILs may facilitate early selection of poor responders for alternative treatment strategies.

Interplay between Caveolin-1 and body and tumor size affects clinical outcomes in breast cancer.

BACKGROUND: Caveolin-1 (CAV1) is associated with cholesterol-rich membrane raft domains and is a master regulator of cell signaling and membrane transport. Here, we investigated CAV1's role in cellular compartments of breast cancer in relation to signaling pathways, clinicopathological features, and clinical outcomes. METHODS: CAV1 levels were evaluated with immunohistochemistry in cytoplasm of invasive tumor cells and stromal cells in tumor tissue microarrays from a cohort of 1018 breast cancer patients (inclusion 2002-2012, Sweden). Cytoplasmic and stromal CAV1 were categorized as positive/negative and strong/not strong, respectively. CAV1 expression in relation to clinical outcomes was assessed with Cox regression. Investigations into CAV1 functional pathways was conducted in the STRING, GOBO, and TCGA databases. RESULTS: CAV1 expression was associated with non-luminal subtypes, cell cycle control, inflammation, epithelial-mesenchymal transition, and the IGF/Insulin system. Generally, CAV1 was not associated with recurrence risk. Stromal CAV1's impact on recurrence risk was modified by BMI ≥25 kg/m2 (Pinteraction = 0.002), waist ≥80 cm (Pinteraction = 0.005), and invasive tumor size (pT2/3/4) (Pinteraction = 0.028). In low-risk patients only, strong stromal CAV1 significantly increased recurrence risk (HRsadj ≥1.61). In all patients, positive cytoplasmic CAV1 conferred >2-fold risk for contralateral disease HRadj 2.63 (95% CI 1.36-5.10). Strong stromal CAV1 conferred nearly 2-fold risk for locoregional recurrence HRadj 1.88 (95% CI 1.09-3.24). CONCLUSIONS: CAV1's prognostic impact depended on its localization, anthropometric, and tumor factors. Stromal CAV1 predicted high recurrence risk in a group of supposedly 'low-risk' patients. Cytoplasmic CAV1 predicted metachronous contralateral disease. If confirmed, CAV1 could be used as treatment target and for risk-stratification.

Prognostic impact of tumor-specific insulin-like growth factor binding protein 7 (IGFBP7) levels in breast cancer: a prospective cohort study.

The prognostic impact of insulin-like growth factor binding protein 7 (IGFBP7) in breast cancer is unclear. Host factors, including lifestyle, anthropometry and metabolic profile, might influence tumor-specific IGFBP7. This study aimed to investigate whether IGFBP7 levels and messenger ribonucleic acid (mRNA) expression are associated with the patient and tumor characteristics and prognosis in breast cancer. Patients with primary breast cancer in Lund, Sweden, were included preoperatively in the study between 2002 and 2012 (n = 1018). Tumor-specific IGFBP7 protein levels were evaluated with immunohistochemistry using tissue microarrays in tumors from 878 patients. IGFBP7 mRNA expression and its corresponding clinical data were obtained from The Cancer Genome Atlas and analyzed for 809 patients. Tumor-specific IGFBP7 protein levels were categorized based on Histo 300 scores into IGFBP7low (6.2%), IGFBP7intermediate (75.7%) and IGFBP7high (18.1%). Both low IGFBP7 protein levels and mRNA expression were associated with less aggressive tumor characteristics. Overall, IGFBP7low conferred low recurrence risk. The prognostic impact of IGFBP7high varied according to any alcohol consumption and tamoxifen treatment. IGFBP7high was associated with low recurrence risk in alcohol consumers but high recurrence risk in alcohol abstainers (Pinteraction= 0.039). Moreover, the combination of IGFBP7high and estrogen receptor-positive tumors was associated with low recurrence risk only in tamoxifen-treated patients (Pinteraction= 0.029). To conclude, IGFBP7low might be a good, independent prognosticator in breast cancer. The prognostic impact of IGFBP7high depends on host factors and treatment. IGFBP7 merits further investigation to confirm whether it could be a suitable biomarker for treatment selection.

Co-targeting CDK4/6 and AKT with endocrine therapy prevents progression in CDK4/6 inhibitor and endocrine therapy-resistant breast cancer.

CDK4/6 inhibitors (CDK4/6i) combined with endocrine therapy have shown impressive efficacy in estrogen receptor-positive advanced breast cancer. However, most patients will eventually experience disease progression on this combination, underscoring the need for effective subsequent treatments or better initial therapies. Here, we show that triple inhibition with fulvestrant, CDK4/6i and AKT inhibitor (AKTi) durably impairs growth of breast cancer cells, prevents progression and reduces metastasis of tumor xenografts resistant to CDK4/6i-fulvestrant combination or fulvestrant alone. Importantly, switching from combined fulvestrant and CDK4/6i upon resistance to dual combination with AKTi and fulvestrant does not prevent tumor progression. Furthermore, triple combination with AKTi significantly inhibits growth of patient-derived xenografts resistant to combined CDK4/6i and fulvestrant. Finally, high phospho-AKT levels in metastasis of breast cancer patients treated with a combination of CDK4/6i and endocrine therapy correlates with shorter progression-free survival. Our findings support the clinical development of ER, CDK4/6 and AKT co-targeting strategies following progression on CDK4/6i and endocrine therapy combination, and in tumors exhibiting high phospho-AKT levels, which are associated with worse clinical outcome.

An Open-Source, Automated Tumor-Infiltrating Lymphocyte Algorithm for Prognosis in Triple-Negative Breast Cancer.

PURPOSE: Although tumor-infiltrating lymphocytes (TIL) assessment has been acknowledged to have both prognostic and predictive importance in triple-negative breast cancer (TNBC), it is subject to inter and intraobserver variability that has prevented widespread adoption. Here we constructed a machine-learning based breast cancer TIL scoring approach and validated its prognostic potential in multiple TNBC cohorts. EXPERIMENTAL DESIGN: Using the QuPath open-source software, we built a neural-network classifier for tumor cells, lymphocytes, fibroblasts, and "other" cells on hematoxylin-eosin (H&E)-stained sections. We analyzed the classifier-derived TIL measurements with five unique constructed TIL variables. A retrospective collection of 171 TNBC cases was used as the discovery set to identify the optimal association of machine-read TIL variables with patient outcome. For validation, we evaluated a retrospective collection of 749 TNBC patients comprised of four independent validation subsets. RESULTS: We found that all five machine TIL variables had significant prognostic association with outcomes (P ≤ 0.01 for all comparisons) but showed cell-specific variation in validation sets. Cox regression analysis demonstrated that all five TIL variables were independently associated with improved overall survival after adjusting for clinicopathologic factors including stage, age, and histologic grade (P ≤ 0.0003 for all analyses). CONCLUSIONS: Neural net-driven cell classifier-defined TIL variables were robust and independent prognostic factors in several independent validation cohorts of TNBC patients. These objective, open-source TIL variables are freely available to download and can now be considered for testing in a prospective setting to assess clinical utility.See related commentary by Symmans, p. 5446.

Neoadjuvant Trastuzumab, Pertuzumab, and Docetaxel vs Trastuzumab Emtansine in Patients With ERBB2-Positive Breast Cancer: A Phase 2 Randomized Clinical Trial.

Importance: Trastuzumab emtansine (T-DM1) is presently approved for treatment of advanced breast cancer and after incomplete response to neoadjuvant therapy, but the potential of T-DM1 as monotherapy is so far unknown. Objective: To assess pathologic complete response (pCR) to standard neoadjuvant therapy of combination docetaxel, trastuzumab, and pertuzumab (DTP) vs T-DM1 monotherapy in patients with ERBB2 (formerly HER2)-positive breast cancer. Design, Setting, and Participants: This randomized phase 2 trial, conducted at 9 sites in Sweden, enrolled 202 patients between December 1, 2014, and October 31, 2018. Participants were 18 years or older, with ERBB2-positive tumors larger than 20 mm and/or verified lymph node metastases. Analysis was performed on an intention-to-treat basis. Interventions: Patients were randomized to receive 6 cycles of DTP (standard group) or T-DM1 (investigational group). Crossover was recommended at lack of response or occurrence of intolerable toxic effects. Assessment with fluorine 18-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography combined with computed tomography (PET-CT) was performed at baseline and after 2 and 6 treatment cycles. Main Outcome and Measures: Pathologic complete response, defined as ypT0 or Tis ypN0. Secondary end points were clinical and radiologic objective response; event-free survival, invasive disease-free survival, distant disease-free survival, and overall survival; safety; health-related quality of life (HRQoL); functional and biological tumor characteristics; and frequency of breast-conserving surgery. Results: Overall, 202 patients were randomized; 197 (99 women in the standard group [median age, 51 years (range, 26-73 years)] and 98 women in the investigational group [median age, 53 years (range, 28-74 years)]) were evaluable for the primary end point. Pathologic complete response was achieved in 45 patients in the standard group (45.5%; 95% CI 35.4%-55.8%) and 43 patients in the investigational group (43.9%; 95% CI 33.9%-54.3%). The difference was not statistically significant (P = .82). In a subgroup analysis, the pCR rate was higher in hormone receptor-negative tumors than in hormone receptor-positive tumors in both treatment groups (45 of 72 [62.5%] vs 45 of 125 [36.0%]). Three patients in the T-DM1 group experienced progression during therapy. In an exploratory analysis, tumor-infiltrating lymphocytes at 10% or more (median) estimated pCR significantly (odds ratio, 2.76; 95% CI, 1.42-5.36; P = .003). Response evaluation with 18F-FDG PET-CT revealed a relative decrease of maximum standardized uptake value by equal to or greater than 68.7% (median) was associated with pCR (odds ratio, 6.74, 95% CI, 2.75-16.51; P < .001). Conclusions and Relevance: In this study, treatment with standard neoadjuvant combination DTP was equal to T-DM1. Trial Registrations: ClinicalTrials.gov Identifier: NCT02568839; EudraCT number: 2014-000808-10.

Oncogenic translation directs spliceosome dynamics revealing an integral role for SF3A3 in breast cancer.

Splicing is a central RNA-based process commonly altered in human cancers; however, how spliceosomal components are co-opted during tumorigenesis remains poorly defined. Here we unravel the core splice factor SF3A3 at the nexus of a translation-based program that rewires splicing during malignant transformation. Upon MYC hyperactivation, SF3A3 levels are modulated translationally through an RNA stem-loop in an eIF3D-dependent manner. This ensures accurate splicing of mRNAs enriched for mitochondrial regulators. Altered SF3A3 translation leads to metabolic reprogramming and stem-like properties that fuel MYC tumorigenic potential in vivo. Our analysis reveals that SF3A3 protein levels predict molecular and phenotypic features of aggressive human breast cancers. These findings unveil a post-transcriptional interplay between splicing and translation that governs critical facets of MYC-driven oncogenesis.

Distinct mechanisms of resistance to fulvestrant treatment dictate level of ER independence and selective response to CDK inhibitors in metastatic breast cancer.

BACKGROUND: Resistance to endocrine treatment in metastatic breast cancer is a major clinical challenge. Clinical tools to predict both drug resistance and possible treatment combination approaches to overcome it are lacking. This unmet need is mainly due to the heterogeneity underlying both the mechanisms involved in resistance development and breast cancer itself. METHODS: To study the complexity of the mechanisms involved in the resistance to the selective estrogen receptor degrader (SERD) fulvestrant, we performed comprehensive biomarker analyses using several in vitro models that recapitulate the heterogeneity of developed resistance. We further corroborated our findings in tissue samples from patients treated with fulvestrant. RESULTS: We found that different in vitro models of fulvestrant resistance show variable stability in their phenotypes, which corresponded with distinct genomic alterations. Notably, the studied models presented adaptation at different cell cycle nodes to facilitate progression through the cell cycle and responded differently to CDK inhibitors. Cyclin E2 overexpression was identified as a biomarker of a persistent fulvestrant-resistant phenotype. Comparison of pre- and post-treatment paired tumor biopsies from patients treated with fulvestrant revealed an upregulation of cyclin E2 upon development of resistance. Moreover, overexpression of this cyclin was found to be a prognostic factor determining resistance to fulvestrant and shorter progression-free survival. CONCLUSIONS: These data highlight the complexity of estrogen receptor positive breast cancer and suggest that the development of diverse resistance mechanisms dictate levels of ER independence and potentially cross-resistance to CDK inhibitors.

Comprehensive molecular comparison of BRCA1 hypermethylated and BRCA1 mutated triple negative breast cancers.

Homologous recombination deficiency (HRD) is a defining characteristic in BRCA-deficient breast tumors caused by genetic or epigenetic alterations in key pathway genes. We investigated the frequency of BRCA1 promoter hypermethylation in 237 triple-negative breast cancers (TNBCs) from a population-based study using reported whole genome and RNA sequencing data, complemented with analyses of genetic, epigenetic, transcriptomic and immune infiltration phenotypes. We demonstrate that BRCA1 promoter hypermethylation is twice as frequent as BRCA1 pathogenic variants in early-stage TNBC and that hypermethylated and mutated cases have similarly improved prognosis after adjuvant chemotherapy. BRCA1 hypermethylation confers an HRD, immune cell type, genome-wide DNA methylation, and transcriptional phenotype similar to TNBC tumors with BRCA1-inactivating variants, and it can be observed in matched peripheral blood of patients with tumor hypermethylation. Hypermethylation may be an early event in tumor development that progress along a common pathway with BRCA1-mutated disease, representing a promising DNA-based biomarker for early-stage TNBC.

Whole-genome sequencing of triple-negative breast cancers in a population-based clinical study.

Whole-genome sequencing (WGS) brings comprehensive insights to cancer genome interpretation. To explore the clinical value of WGS, we sequenced 254 triple-negative breast cancers (TNBCs) for which associated treatment and outcome data were collected between 2010 and 2015 via the population-based Sweden Cancerome Analysis Network-Breast (SCAN-B) project (ClinicalTrials.gov ID:NCT02306096). Applying the HRDetect mutational-signature-based algorithm to classify tumors, 59% were predicted to have homologous-recombination-repair deficiency (HRDetect-high): 67% explained by germline/somatic mutations of BRCA1/BRCA2, BRCA1 promoter hypermethylation, RAD51C hypermethylation or biallelic loss of PALB2. A novel mechanism of BRCA1 abrogation was discovered via germline SINE-VNTR-Alu retrotransposition. HRDetect provided independent prognostic information, with HRDetect-high patients having better outcome on adjuvant chemotherapy for invasive disease-free survival (hazard ratio (HR) = 0.42; 95% confidence interval (CI) = 0.2-0.87) and distant relapse-free interval (HR = 0.31, CI = 0.13-0.76) compared to HRDetect-low, regardless of whether a genetic/epigenetic cause was identified. HRDetect-intermediate, some possessing potentially targetable biological abnormalities, had the poorest outcomes. HRDetect-low cancers also had inadequate outcomes: ~4.7% were mismatch-repair-deficient (another targetable defect, not typically sought) and they were enriched for (but not restricted to) PIK3CA/AKT1 pathway abnormalities. New treatment options need to be considered for now-discernible HRDetect-intermediate and HRDetect-low categories. This population-based study advocates for WGS of TNBC to better inform trial stratification and improve clinical decision-making.

The X-Linked DDX3X RNA Helicase Dictates Translation Reprogramming and Metastasis in Melanoma.

The X-linked DDX3X gene encodes an ATP-dependent DEAD-box RNA helicase frequently altered in various human cancers, including melanomas. Despite its important roles in translation and splicing, how DDX3X dysfunction specifically rewires gene expression in melanoma remains completely unknown. Here, we uncover a DDX3X-driven post-transcriptional program that dictates melanoma phenotype and poor disease prognosis. Through an unbiased analysis of translating ribosomes, we identified the microphthalmia-associated transcription factor, MITF, as a key DDX3X translational target that directs a proliferative-to-metastatic phenotypic switch in melanoma cells. Mechanistically, DDX3X controls MITF mRNA translation via an internal ribosome entry site (IRES) embedded within the 5' UTR. Through this exquisite translation-based regulatory mechanism, DDX3X steers MITF protein levels dictating melanoma metastatic potential in vivo and response to targeted therapy. Together, these findings unravel a post-transcriptional layer of gene regulation that may provide a unique therapeutic vulnerability in aggressive male melanomas.

The Strategy of PIKing a Target: What Is AKTually Most Effective?

Breast and gynecologic cancers harboring PIK3CA mutations showed no significant responses to AZD5363, a pan-AKT catalytic inhibitor, in contrast with previous in vitro data showing activity of the drug in this subset of cancers. These results raise the question of how to select the most accurate predictive biomarkers of response. Clin Cancer Res; 24(9); 2029-31. ©2018 AACRSee related article by Banerji et al., p. 2050.

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

High expression of cholesterol biosynthesis genes is associated with resistance to statin treatment and inferior survival in breast cancer.

There is sufficient evidence that statins have a protective role against breast cancer proliferation and recurrence, but treatment predictive biomarkers are lacking. Breast cancer cell lines displaying diverse sensitivity to atorvastatin were subjected to global transcriptional profiling and genes significantly altered by statin treatment were identified. Atorvastatin treatment strongly inhibited proliferation in estrogen receptor (ER) negative cell lines and a commensurate response was also evident on the genome-wide transcriptional scale, with ER negative cells displaying a robust deregulation of genes involved in the regulation of cell cycle progression and apoptosis. Interestingly, atorvastatin upregulated genes involved in the cholesterol biosynthesis pathway in all cell lines, irrespective of sensitivity to statin treatment. However, the level of pathway induction; measured as the fold change in transcript levels, was inversely correlated to the effect of statin treatment on cell growth. High expression of cholesterol biosynthesis genes before treatment was associated with resistance to statin therapy in cell lines and clinical biopsies. Furthermore, high expression of cholesterol biosynthesis genes was independently prognostic for a shorter recurrence-free and overall survival, especially among ER positive tumors. Dysregulation of cholesterol biosynthesis is therefore predictive for both sensitivity to anti-cancer statin therapy and prognosis following primary breast cancer diagnosis.