Predictability of B cell clonal persistence and immunosurveillance in breast cancer.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Virus-like particle-mediated delivery of structure-selected neoantigens demonstrates immunogenicity and antitumoral activity in mice.

BACKGROUND: Neoantigens are patient- and tumor-specific peptides that arise from somatic mutations. They stand as promising targets for personalized therapeutic cancer vaccines. The identification process for neoantigens has evolved with the use of next-generation sequencing technologies and bioinformatic tools in tumor genomics. However, in-silico strategies for selecting immunogenic neoantigens still have very low accuracy rates, since they mainly focus on predicting peptide binding to Major Histocompatibility Complex (MHC) molecules, which is key but not the sole determinant for immunogenicity. Moreover, the therapeutic potential of neoantigen-based vaccines may be enhanced using an optimal delivery platform that elicits robust de novo immune responses. METHODS: We developed a novel neoantigen selection pipeline based on existing software combined with a novel prediction method, the Neoantigen Optimization Algorithm (NOAH), which takes into account structural features of the peptide/MHC-I interaction, as well as the interaction between the peptide/MHC-I complex and the TCR, in its prediction strategy. Moreover, to maximize neoantigens' therapeutic potential, neoantigen-based vaccines should be manufactured in an optimal delivery platform that elicits robust de novo immune responses and bypasses central and peripheral tolerance. RESULTS: We generated a highly immunogenic vaccine platform based on engineered HIV-1 Gag-based Virus-Like Particles (VLPs) expressing a high copy number of each in silico selected neoantigen. We tested different neoantigen-loaded VLPs (neoVLPs) in a B16-F10 melanoma mouse model to evaluate their capability to generate new immunogenic specificities. NeoVLPs were used in in vivo immunogenicity and tumor challenge experiments. CONCLUSIONS: Our results indicate the relevance of incorporating other immunogenic determinants beyond the binding of neoantigens to MHC-I. Thus, neoVLPs loaded with neoantigens enhancing the interaction with the TCR can promote the generation of de novo antitumor-specific immune responses, resulting in a delay in tumor growth. Vaccination with the neoVLP platform is a robust alternative to current therapeutic vaccine approaches and a promising candidate for future personalized immunotherapy.

Modeling the Prognostic Impact of Circulating Tumor Cells Enumeration in Metastatic Breast Cancer for Clinical Trial Design Simulation.

Despite the strong prognostic stratification of circulating tumor cells (CTCs) enumeration in metastatic breast cancer (MBC), current clinical trials usually do not include a baseline CTCs in their design. This study aimed to generate a classifier for CTCs prognostic simulation in existing datasets for hypothesis generation in patients with MBC. A K-nearest neighbor machine learning algorithm was trained on a pooled dataset comprising 2436 individual MBC patients from the European Pooled Analysis Consortium and the MD Anderson Cancer Center to identify patients likely to have CTCs ≥ 5/7 mL blood (StageIVaggressive vs StageIVindolent). The model had a 65.1% accuracy and its prognostic impact resulted in a hazard ratio (HR) of 1.89 (Simulatedaggressive vs SimulatedindolentP < .001), similar to patients with actual CTCs enumeration (HR 2.76; P < .001). The classifier's performance was then tested on an independent retrospective database comprising 446 consecutive hormone receptor (HR)-positive HER2-negative MBC patients. The model further stratified clinical subgroups usually considered prognostically homogeneous such as patients with bone-only or liver metastases. Bone-only disease classified as Simulatedaggressive had a significantly worse overall survival (OS; P < .0001), while patients with liver metastases classified as Simulatedindolent had a significantly better prognosis (P < .0001). Consistent results were observed for patients who had undergone CTCs enumeration in the pooled population. The differential prognostic impact of endocrine- (ET) and chemotherapy (CT) was explored across the simulated subgroups. No significant differences were observed between ET and CT in the overall population, both in terms of progression-free survival (PFS) and OS. In contrast, a statistically significant difference, favoring CT over ET was observed among Simulatedaggressive patients (HR: 0.62; P = .030 and HR: 0.60; P = .037, respectively, for PFS and OS).

Cumulus cell antioxidant system is modulated by patients' clinical characteristics and correlates with embryo development.

PURPOSE: To study whether the cumulus cell antioxidant system varies accordingly to patients clinical characteristics' as age, infertility diagnosis, BMI, and stimulation protocol applied and if the antioxidant profile of cumulus cells could be used as a predictor of embryo development. METHODS: A prospective study including 383 human cumulus samples provided by 191 female patients undergoing intracytoplasmic sperm injection during in vitro fertilization treatments from a local in vitro fertilization center and processed in university laboratories. Catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), and glutathione S-transferase (GST) enzyme activity levels and reduced glutathione (GSH) levels were measured in cumulus oophorus cells individually collected from each aspirated cumulus-oocyte complex, and the results of each sample were compared considering the oocytes outcome after ICSI and patients clinical characteristics. A total of 223 other human cumulus samples from previous studies were submitted to a gene expression meta-analysis. RESULTS: The antioxidant system changes dramatically depending on patients' age, infertility diagnosis, stimulation protocol applied, and oocyte quality. SOD activity in cumulus cells revealed to be predictive of top-quality blastocysts for young patients with male factor infertility (P < 0.05), while GST levels were shown to be extremely influenced by infertility cause (P < 0.0001) and stimulation protocol applied (P < 0.05), but nonetheless, it can be used as a complementary tool for top-quality blastocyst prediction in patients submitted to intracytoplasmic sperm injection technique (ICSI) by male factor infertility (P < 0.05). CONCLUSION: Through a simple and non-invasive analysis, the evaluation of redox enzymes in cumulus cells could be used to predict embryo development, in a personalized matter in specific patient groups, indicating top-quality oocytes and improving success rates in in vitro fertilization treatments. TRIAL REGISTRATION: The trial was registered at UFRGS Research Ethics Committee and Plataforma Brasil under approval number 68081017.2.0000.5347 in June 6, 2019.

Cancer as an ecomolecular disease and a neoplastic consortium.

Current anticancer paradigms largely target driver mutations considered integral for cancer cell survival and tumor progression. Although initially successful, many of these strategies are unable to overcome the tremendous heterogeneity that characterizes advanced tumors, resulting in the emergence of resistant disease. Cancer is a rapidly evolving, multifactorial disease that accumulates numerous genetic and epigenetic alterations. This results in wide phenotypic and molecular heterogeneity within the tumor, the complexity of which is further amplified through specific interactions between cancer cells and the tumor microenvironment. In this context, cancer may be perceived as an "ecomolecular" disease that involves cooperation between several neoplastic clones and their interactions with immune cells, stromal fibroblasts, and other cell types present in the microenvironment. This collaboration is mediated by a variety of secreted factors. Cancer is therefore analogous to complex ecosystems such as microbial consortia. In the present article, we comment on the current paradigms and perspectives guiding the development of cancer diagnostics and therapeutics and the potential application of systems biology to untangle the complexity of neoplasia. In our opinion, conceptualization of neoplasia as an ecomolecular disease is warranted. Advances in knowledge pertinent to the complexity and dynamics of interactions within the cancer ecosystem are likely to improve understanding of tumor etiology, pathogenesis, and progression. This knowledge is anticipated to facilitate the design of new and more effective therapeutic approaches that target the tumor ecosystem in its entirety.

The repertoire of somatic genetic alterations of acinic cell carcinomas of the breast: an exploratory, hypothesis-generating study.

Acinic cell carcinoma (ACC) of the breast is a rare form of triple-negative (that is, oestrogen receptor-negative, progesterone receptor-negative, HER2-negative) salivary gland-type tumour displaying serous acinar differentiation. Despite its triple-negative phenotype, breast ACCs are reported to have an indolent clinical behaviour. Here, we sought to define whether ACCs have a mutational repertoire distinct from that of other triple-negative breast cancers (TNBCs). DNA was extracted from microdissected formalin-fixed, paraffin-embedded sections of tumour and normal tissue from two pure and six mixed breast ACCs. Each tumour component of the mixed cases was microdissected separately. Tumour and normal samples were subjected to targeted capture massively parallel sequencing targeting all exons of 254 genes, including genes most frequently mutated in breast cancer and related to DNA repair. Selected somatic mutations were validated by targeted amplicon resequencing and Sanger sequencing. Akin to other forms of TNBC, the most frequently mutated gene found in breast ACCs was TP53 (one pure and six mixed cases). Additional somatic mutations affecting breast cancer-related genes found in ACCs included PIK3CA, MTOR, CTNNB1, BRCA1, ERBB4, ERBB3, INPP4B, and FGFR2. Copy number alteration analysis revealed complex patterns of gains and losses similar to those of common forms of TNBCs. Of the mixed cases analysed, identical somatic mutations were found in the acinic and the high-grade non-acinic components in two out of four cases analysed, providing evidence of their clonal relatedness. In conclusion, breast ACCs display the hallmark somatic genetic alterations found in high-grade forms of TNBC, including complex patterns of gene copy number alterations and recurrent TP53 mutations. Furthermore, we provide circumstantial genetic evidence to suggest that ACCs may constitute the substrate for the development of more aggressive forms of triple-negative disease.

Recent Progress on Systems and Synthetic Biology Approaches to Engineer Fungi As Microbial Cell Factories.

Filamentous fungi are remarkable organisms naturally specialized in deconstructing plant biomass and this feature has a tremendous potential for biofuel production from renewable sources. The past decades have been marked by a remarkable progress in the genetic engineering of fungi to generate industry-compatible strains needed for some biotech applications. In this sense, progress in this field has been marked by the utilization of high-throughput techniques to gain deep understanding of the molecular machinery controlling the physiology of these organisms, starting thus the Systems Biology era of fungi. Additionally, genetic engineering has been extensively applied to modify wellcharacterized promoters in order to construct new expression systems with enhanced performance under the conditions of interest. In this review, we discuss some aspects related to significant progress in the understating and engineering of fungi for biotechnological applications, with special focus on the construction of synthetic promoters and circuits in organisms relevant for industry. Different engineering approaches are shown, and their potential and limitations for the construction of complex synthetic circuits in these organisms are examined. Finally, we discuss the impact of engineered promoter architecture in the single-cell behavior of the system, an often-neglected relationship with a tremendous impact in the final performance of the process of interest. We expect to provide here some new directions to drive future research directed to the construction of high-performance, engineered fungal strains working as microbial cell factories.

Are acinic cell carcinomas of the breast and salivary glands distinct diseases?

AIMS: Acinic cell carcinomas (AcCC) of the breast have been reported to constitute the breast counterpart of salivary gland AcCCs, based on the similarities of their histological and immunohistochemical features. Breast AcCC is a vanishingly rare form of triple-negative breast cancer (TNBC). Recent studies have demonstrated that in TNBCs, the two driver genes most frequently mutated are TP53 (82%) and PIK3CA (10%). We sought to define whether breast AcCCs would harbour TP53 and PIK3CA somatic mutations, and if so, whether these would be present in salivary gland AcCCs. METHODS AND RESULTS: Sanger sequencing of the entire coding region of TP53 and of PIK3CA hotspot mutation sites of 10 breast and 20 salivary gland microdissected AcCCs revealed eight TP53 (80%) and one PIK3CA (10%) somatic mutations in breast AcCCs. No somatic mutations affecting these genes were found in the 20 salivary gland AcCCs analysed. CONCLUSIONS: Our findings demonstrate that breast AcCCs display TP53 and PIK3CA mutations at frequencies similar to those of common types of TNBCs, whereas these genes appear not to be altered in salivary gland AcCCs, suggesting that despite their similar histological appearances, AcCCs of the breast and salivary glands probably constitute unrelated diseases.

Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data.

BACKGROUND: We aimed to assess the clinical validity of circulating tumour cell (CTC) quantification for prognostication of patients with metastatic breast cancer by undertaking a pooled analysis of individual patient data. METHODS: We contacted 51 European centres and asked them to provide reported and unreported anonymised data for individual patients with metastatic breast cancer who participated in studies between January, 2003, and July, 2012. Eligible studies had participants starting a new line of therapy, data for progression-free survival or overall survival, or both, and CTC quantification by the CellSearch method at baseline (before start of new treatment). We used Cox regression models, stratified by study, to establish the association between CTC count and progression-free survival and overall survival. We used the landmark method to assess the prognostic value of CTC and serum marker changes during treatment. We assessed the added value of CTCs or serum markers to prognostic clinicopathological models in a resampling procedure using likelihood ratio (LR) χ(2) statistics. FINDINGS: 17 centres provided data for 1944 eligible patients from 20 studies. 911 patients (46·9%) had a CTC count of 5 per 7·5 mL or higher at baseline, which was associated with decreased progression-free survival (hazard ratio [HR] 1·92, 95% CI 1·73-2·14, p<0·0001) and overall survival (HR 2·78, 95% CI 2·42-3·19, p<0·0001) compared with patients with a CTC count of less than 5 per 7·5 mL at baseline. Increased CTC counts 3-5 weeks after start of treatment, adjusted for CTC count at baseline, were associated with shortened progression-free survival (HR 1·85, 95% CI 1·48-2·32, p<0·0001) and overall survival (HR 2·26, 95% CI 1·68-3·03) as were increased CTC counts after 6-8 weeks (progression-free survival HR 2·20, 95% CI 1·66-2·90, p<0·0001; overall survival HR 2·91, 95% CI 2·01-4·23, p<0·0001). Survival prediction was significantly improved by addition of baseline CTC count to the clinicopathological models (progression-free survival LR 38·4, 95% CI 21·9-60·3, p<0·0001; overall survival LR 64·9, 95% CI 41·3-93·4, p<0·0001). This model was further improved by addition of CTC change at 3-5 weeks (progression-free survival LR 8·2, 95% CI 0·78-20·4, p=0·004; overall survival LR 11·5, 95% CI 2·6-25·1, p=0·0007) and at 6-8 weeks (progression-free survival LR 15·3, 95% CI 5·2-28·3; overall survival LR 14·6, 95% CI 4·0-30·6; both p<0·0001). Carcinoembryonic antigen and cancer antigen 15-3 concentrations at baseline and during therapy did not add significant information to the best baseline model. INTERPRETATION: These data confirm the independent prognostic effect of CTC count on progression-free survival and overall survival. CTC count also improves the prognostication of metastatic breast cancer when added to full clinicopathological predictive models, whereas serum tumour markers do not. FUNDING: Janssen Diagnostics, the Nuovo-Soldati foundation for cancer research.

Converging and evolving immuno-genomic routes toward immune escape in breast cancer.

The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Pilot studies for personalized cancer medicine: focusing on the patient for treatment selection.

Advances in diagnostics and targeted therapies during the past decade have changed how oncology is viewed. "Stratified medicine" has emerged from the accumulated evidence garnered from matching targeted therapies with tumor molecular aberrations. Concomitantly, current knowledge derived from large-scale, massively parallel sequencing technologies and global research initiatives such as the international 1000 Genomes Project, the Cancer Genome Atlas, the International Cancer Genome Consortium, and publicly available catalogs such as the Catalogue of Somatic Mutations in Cancer and Genomics of Drug Sensitivity in Cancer have illuminated the utility of understanding the molecular basis of cancer through genome analysis. In addition, multiple collaborative efforts are widening the possibility of universally personalizing cancer care. Although several key challenges of personalized cancer medicine (PCM) need to be addressed, some pilot studies are transforming the way we analyze tumor tissue molecular aberrations, design clinical trials, and measure treatment efficacy. Taken together, these pilot studies are paving the way for clinical trials that are designed to empirically test the concept of PCM. In this paper, we describe lessons learned from the first pilot initiatives of PCM and how this knowledge is being used to design novel clinical trials.

Bioinformatic Analysis of Human Cumulus Cells to Unravel Cellular's Processes that Could Be Used to Establish Oocyte Quality Biomarkers with Clinical Application.

Metadata analysis of public microarray datasets using bioinformatics tools has been successfully used in several biomedical fields in the search for biomarkers. In reproductive science, there is an urgent need for the establishment of oocyte quality biomarkers that could be used in the clinical environment to increase the chances of successful outcomes in treatment cycles. Adaptive cellular processes observed in cumulus oophorus cells reflect the conditions of the follicular microenvironment and may thus bring relevant information of oocyte's conditions. Here we analyzed human cumulus cells gene expression datasets in search of predictors of oocyte quality, a strategy which uncovered several cellular processes positively and negatively associated with embryo development and pregnancy potential. Secondly, the expression levels of genes that were present in the majority of processes observed were validated in house with clinical samples. Our data confirmed the association of the selected biomarkers with blastocyst formation and pregnancy potential rates, independently of patients' clinical characteristics such as diagnosis, age, BMI, and stimulation protocol applied. This study shows that bioinformatic analysis of cellular processes can be successfully used to elucidate possible oocyte quality biomarkers. Our data reinforces the need to consider clinical characteristics of patients when selecting relevant biomarkers to be used in the clinical environment and suggests a combination of positive (PTGS2) and negative (CYPB1) quality biomarkers as a robust strategy for a complementary oocyte selection tool, potentially increasing assisted reproduction success rates. Also, GPX4 expression as pregnancy potential biomarker is indicated here as a possibility for further investigations.

Advances in first-line treatment for patients with HER-2+ metastatic breast cancer.

BACKGROUND: The prognosis for breast cancer patients overexpressing human epidermal growth factor receptor (HER)-2 has changed with anti-HER-2-targeted therapy. Although anti-HER-2 therapy with trastuzumab and chemotherapy is the standard first-line treatment, the best therapeutic regimen has yet to be defined, and new strategies are evolving. METHODS: A literature review of well-established and recently published trials, reviews, and ongoing clinical trials addressing first-line treatment for HER-2(+) metastatic breast cancer patients was performed. RESULTS: Taxanes are the agents most commonly used in combination with trastuzumab, but other chemotherapy drugs, such as anthracyclines, vinorelbine, and gemcitabine and triple-combination therapies including platinum compounds, capecitabine, and taxanes have been studied. The combination of aromatase inhibitors with anti-HER-2 therapies is a new therapeutic option for some patients who coexpress HER-2 and hormone receptors, although its activity observed in randomized clinical trials seems to be inferior to that of chemotherapy plus anti-HER-2 therapies. In addition, new anti-HER-2 therapies have shown activity in HER-2(+) tumors, both alone and in combination with trastuzumab. CONCLUSIONS: Trastuzumab plus chemotherapy is the current standard of care for the upfront treatment of HER-2(+) breast cancer patients, though other anti-HER-2-targeting agents may appear as new standards in the upcoming years.

Meningeal dendritic cells drive neuropathic pain through elevation of the kynurenine metabolic pathway in mice.

Neuropathic pain is one of the most important clinical consequences of injury to the somatosensory system. Nevertheless, the critical pathophysiological mechanisms involved in neuropathic pain development are poorly understood. In this study, we found that neuropathic pain is abrogated when the kynurenine metabolic pathway (KYNPATH) initiated by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1) is ablated pharmacologically or genetically. Mechanistically, it was found that IDO1-expressing dendritic cells (DCs) accumulated in the dorsal root leptomeninges and led to an increase in kynurenine levels in the spinal cord. In the spinal cord, kynurenine was metabolized by kynurenine-3-monooxygenase-expressing astrocytes into the pronociceptive metabolite 3-hydroxykynurenine. Ultimately, 3-hydroxyanthranilate 3,4-dioxygenase-derived quinolinic acid formed in the final step of the canonical KYNPATH was also involved in neuropathic pain development through the activation of the glutamatergic N-methyl-D-aspartate receptor. In conclusion, these data revealed a role for DCs driving neuropathic pain development through elevation of the KYNPATH. This paradigm offers potential new targets for drug development against this type of chronic pain.

Genome sequence of the diazotrophic Gram-positive rhizobacterium Paenibacillus riograndensis SBR5(T).

Paenibacillus riograndensis SBR5(T), a nitrogen-fixing Gram-positive rhizobacterium isolated from a wheat field in the south of Brazil, has a great potential for agricultural applications due to its plant growth promotion effects. Here we present the draft genome sequence of P. riograndensis SBR5(T). Its 7.37-Mb genome encodes determinants of the diazotrophic lifestyle and plant growth promotion, such as nitrogen fixation, antibiotic resistance, nitrate utilization, and iron uptake.

Prognostic and predictive roles for circulating biomarkers in gastrointestinal cancer.

Circulating tumor cells (CTCs) and circulating free DNA (cfDNA) have been studied as promising prognostic and predictive tumor-derived biomarkers in the bloodstream of patients with gastrointestinal malignancies because they may be an alternative noninvasive tool to tumor tissue biopsies. Quantification and molecular characterization of CTCs and cfDNA may provide additional insights into cancer biology, potentially revealing novel targets to individualize cancer care. The present article aims to review the biology and current methods to assess CTCs and cfDNA, and the efforts to establish both tumor-derived biomarkers as prognostic and predictive factors in esophageal, gastric and colorectal cancer.

Immune analysis of lymph nodes in relation to the presence or absence of tumor infiltrating lymphocytes in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with unmet medical needs. Several studies have proved that high levels of tumor infiltrating lymphocytes (TILs) at diagnosis of TNBC confer better prognosis and patients respond better to specific chemotherapies. Nonetheless, current evidence suggests that only 15% of TNBC patients have very high levels of TILs, and another 15% lacks TILs. One possible reason to explain why patients have low TILs at diagnosis is that lymphocytes might be deactivated by an immune checkpoint in local lymph nodes, provoking their retention in there as they are unresponsive to other immune stimuli. We have identified 15 high TILs (≥50%) and 20 low TILs (≤5%) TNBC patients with localised tumour (T1c-T2N0M0) and compared the protein expression of five immune checkpoints in lymph nodes. We have also performed a customised 50-immune gene NanoString expression panel, the NanoString 360 Breast Cancer panel, and whole exome sequencing for mutation and neoantigen load analyses. In low TILs, we observed higher expression of CTLA-4 in local lymph nodes, which could explain why lymphocytes get retained in there and do not migrate to tumour. These patients have also higher neoantigen load and higher expression of B7.H3 and B7.H4 in the tumour. In high TILs, we observed more PD-L1+ tumour cells and more expanded humoral response. These results could provide a strategy to revert low tumour immune infiltration at diagnosis of TNBC, improving their prognosis.

The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers.

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

Serial Analysis of Circulating Tumor Cells in Metastatic Breast Cancer Receiving First-Line Chemotherapy.

BACKGROUND: We examined the prognostic significance of circulating tumor cell (CTC) dynamics during treatment in metastatic breast cancer (MBC) patients receiving first-line chemotherapy. METHODS: Serial CTC data from 469 patients (2202 samples) were used to build a novel latent mixture model to identify groups with similar CTC trajectory (tCTC) patterns during the course of treatment. Cox regression was used to estimate hazard ratios for progression-free survival (PFS) and overall survival (OS) in groups based on baseline CTCs, combined CTC status at baseline to the end of cycle 1, and tCTC. Akaike information criterion was used to select the model that best predicted PFS and OS. RESULTS: Latent mixture modeling revealed 4 distinct tCTC patterns: undetectable CTCs (56.9% ), low (23.7%), intermediate (14.5%), or high (4.9%). Patients with low, intermediate, and high tCTC patterns had statistically significant inferior PFS and OS compared with those with undetectable CTCs (P < .001). Akaike Information Criterion indicated that the tCTC model best predicted PFS and OS compared with baseline CTCs and combined CTC status at baseline to the end of cycle 1 models. Validation studies in an independent cohort of 1856 MBC patients confirmed these findings. Further validation using only a single pretreatment CTC measurement confirmed prognostic performance of the tCTC model. CONCLUSIONS: We identified 4 novel prognostic groups in MBC based on similarities in tCTC patterns during chemotherapy. Prognostic groups included patients with very poor outcome (intermediate + high CTCs, 19.4%) who could benefit from more effective treatment. Our novel prognostic classification approach may be used for fine-tuning of CTC-based risk stratification strategies to guide future prospective clinical trials in MBC.

New emerging targets in cancer immunotherapy: the role of neoantigens.

The success of cancer therapies with immune checkpoint inhibitors is transforming the treatment of patients with cancer and fostering cancer research. Therapies that target immune checkpoint inhibitors have shown unprecedented rates of durable long-lasting responses in patients with various cancer types, but only in a fraction of patients. Thus, novel approaches are needed to make immunotherapy more precise and also less toxic. The advances of next-generation sequencing technologies have allowed fast detection of somatic mutations in genes present in the exome of an individual tumour. Targeting neoantigens, the mutated peptides expressed only by tumour cells, may enable antitumour T-cell responses and tumour destruction without causing harm to healthy tissues. Currently, neoantigens can be identified in tumour clinical samples by using genomic-based computational tools. The two main treatment modalities targeting neoantigens that have been investigated in clinical trials are personalised vaccines and tumour infiltrating lymphocytes-based adoptive T-cell therapy. In this mini review, we discuss the promises and challenges for using neoantigens as emergent targets to personalise and guide cancer immunotherapy in a broader set of cancers.