Cancer classification using the Immunoscore: a worldwide task force

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).

Plasma biomarkers as predictors of outcome in patients with advanced hepatocellular carcinoma

Validated biomarkers of prognosis and response to drug have not been identified for patients with hepatocellular carcinoma (HCC). One of the objectives of the phase III, randomized, controlled Sorafenib HCC Assessment Randomized Protocol (SHARP) trial was to explore the ability of plasma biomarkers to predict prognosis and therapeutic efficacy.

CA15-3 and alkaline phosphatase as predictors for breast cancer recurrence: a combined analysis of seven International Breast Cancer Study Group trials

BACKGROUND: We evaluated the ability of CA15-3 and alkaline phosphatase (ALP) to predict breast cancer recurrence. PATIENTS AND METHODS: Data from seven International Breast Cancer Study Group trials were combined. The primary end point was relapse-free survival (RFS) (time from randomization to first breast cancer recurrence), and analyses included 3953 patients with one or more CA15-3 and ALP measurement during their RFS period. CA15-3 was considered abnormal if >30 U/ml or >50% higher than the first value recorded; ALP was recorded as normal, abnormal, or equivocal. Cox proportional hazards models with a time-varying indicator for abnormal CA15-3 and/or ALP were utilized. RESULTS: Overall, 784 patients (20%) had a recurrence, before which 274 (35%) had one or more abnormal CA15-3 and 35 (4%) had one or more abnormal ALP. Risk of recurrence increased by 30% for patients with abnormal CA15-3 [hazard ratio (HR) = 1.30; P = 0.0005], and by 4% for those with abnormal ALP (HR = 1.04; P = 0.82). Recurrence risk was greatest for patients with either (HR = 2.40; P < 0.0001) and with both (HR = 4.69; P < 0.0001) biomarkers abnormal. ALP better predicted liver recurrence. CONCLUSIONS: CA15-3 was better able to predict breast cancer recurrence than ALP, but use of both biomarkers together provided a better early indicator of recurrence. Whether routine use of these biomarkers improves overall survival remains an open question.

Alternative splicing of pre-mRNA in cancer: focus on G protein-coupled peptide hormone receptors

Through alternative splicing, multiple different transcripts can be generated from a single gene. Alternative splicing represents an important molecular mechanism of gene regulation in physiological processes such as developmental programming as well as in disease. In cancer, splicing is significantly altered. Tumors express a different collection of alternative spliceoforms than normal tissues. Many tumor-associated splice variants arise from genes with an established role in carcinogenesis or tumor progression, and their functions can be oncogenic. This raises the possibility that products of alternative splicing play a pathogenic role in cancer. Moreover, cancer-associated spliceoforms represent potential diagnostic biomarkers and therapeutic targets. G protein-coupled peptide hormone receptors provide a good illustration of alternative splicing in cancer. The wild-type forms of these receptors have long been known to be expressed in cancer and to modulate tumor cell functions. They are also recognized as attractive clinical targets. Recently, splice variants of these receptors have been increasingly identified in various types of cancer. In particular, alternative cholecystokinin type 2, secretin, and growth hormone-releasing hormone receptor spliceoforms are expressed in tumors. Peptide hormone receptor splice variants can fundamentally differ from their wild-type receptor counterparts in pharmacological and functional characteristics, in their distribution in normal and malignant tissues, and in their potential use for clinical applications.

Bone mineral density and circulating biomarkers in the BIG 1-98 trial comparing adjuvant letrozole, tamoxifen and their sequences.

The purpose of the study is to determine the effects of the BIG 1-98 treatments on bone mineral density. BIG 1-98 compared 5-year adjuvant hormone therapy in postmenopausal women allocated to four groups: tamoxifen (T); letrozole (L); 2-years T, 3-years L (TL); and 2-years L, 3-years T (LT). Bone mineral density T-score was measured prospectively annually by dual energy X-ray absorption in 424 patients enrolled in a sub-study after 3 (n = 150), 4 (n = 200), and 5 years (n = 74) from randomization, and 1 year after treatment cessation. Prevalence of osteoporosis and the association of C-telopeptide, osteocalcin, and bone alkaline phosphatase with T-scores were assessed. At 3 years, T had the highest and TL the lowest T-score. All arms except for LT showed a decline up to 5 years, with TL exhibiting the greatest. At 5 years, there were significant differences on lumbar T-score only between T and TL, whereas for femur T-score, differences were significant for T versus L or TL, and L versus LT. The 5-year prevalence of spine and femur osteoporosis was the highest on TL (14.5 %, 7.1 %) then L (4.3 %, 5.1 %), LT (4.2 %, 1.4 %) and T (4 %, 0). C-telopeptide and osteocalcin were significantly associated with T-scores. While adjuvant L increases bone mineral density loss compared with T, the sequence LT has an acceptable bone safety profile. C-telopeptide and osteocalcin are useful markers of bone density that may be used to monitor bone health during treatment. The sequence LT may be a valid treatment option in patients with low and intermediate risk of recurrence.

Distinct microRNA Expression Profile in Prostate Cancer Patients with Early Clinical Failure and the Impact of let-7 as Prognostic Marker in High-Risk Prostate Cancer

Background The identification of additional prognostic markers to improve risk stratification and to avoid overtreatment is one of the most urgent clinical needs in prostate cancer (PCa). MicroRNAs, being important regulators of gene expression, are promising biomarkers in various cancer entities, though the impact as prognostic predictors in PCa is poorly understood. The aim of this study was to identify specific miRNAs as potential prognostic markers in high-risk PCa and to validate their clinical impact. Methodology and Principal Findings We performed miRNA-microarray analysis in a high-risk PCa study group selected by their clinical outcome (clinical progression free survival (CPFS) vs. clinical failure (CF)). We identified seven candidate miRNAs (let-7a/b/c, miR-515-3p/5p, -181b, -146b, and -361) that showed differential expression between both groups. Further qRT-PCR analysis revealed down-regulation of members of the let-7 family in the majority of a large, well-characterized high-risk PCa cohort (n = 98). Expression of let-7a/b/and -c was correlated to clinical outcome parameters of this group. While let-7a showed no association or correlation with clinical relevant data, let-7b and let-7c were associated with CF in PCa patients and functioned partially as independent prognostic marker. Validation of the data using an independent high-risk study cohort revealed that let-7b, but not let-7c, has impact as an independent prognostic marker for BCR and CF. Furthermore, we identified HMGA1, a non-histone protein, as a new target of let-7b and found correlation of let-7b down-regulation with HMGA1 over-expression in primary PCa samples. Conclusion Our findings define a distinct miRNA expression profile in PCa cases with early CF and identified let-7b as prognostic biomarker in high-risk PCa. This study highlights the importance of let-7b as tumor suppressor miRNA in high-risk PCa and presents a basis to improve individual therapy for high-risk PCa patients.

The additional facet of immunoscore: immunoprofiling as a possible predictive tool for cancer treatment

Recent investigations of the tumor microenvironment have shown that many tumors are infiltrated by inflammatory and lymphocytic cells. Increasing evidence suggests that the number, type and location of these tumor-infiltrating lymphocytes in primary tumors has prognostic value, and this has led to the development of an 'immunoscore. As well as providing useful prognostic information, the immunoscore concept also has the potential to help predict response to treatment, thereby improving decision- making with regard to choice of therapy. This predictive aspect of the tumor microenvironment forms the basis for the concept of immunoprofiling, which can be described as 'using an individual's immune system signature (or profile) to predict that patient's response to therapy' The immunoprofile of an individual can be genetically determined or tumor-induced (and therefore dynamic). Ipilimumab is the first in a series of immunomodulating antibodies and has been shown to be associated with improved overall survival in patients with advanced melanoma. Other immunotherapies in development include anti-programmed death 1 protein (nivolumab), anti-PD-ligand 1, anti-CD137 (urelumab), and anti-OX40. Biomarkers that can be used as predictive factors for these treatments have not yet been clinically validated. However, there is already evidence that the tumor microenvironment can have a predictive role, with clinical activity of ipilimumab related to high baseline expression of the immune-related genes FoxP3 and indoleamine 2,3-dioxygenase and an increase in tumor-infiltrating lymphocytes. These biomarkers could represent the first potential proposal for an immunoprofiling panel in patients for whom anti-CTLA-4 therapy is being considered, although prospective data are required. In conclusion, the evaluation of systemic and local immunological biomarkers could offer useful prognostic information and facilitate clinical decision making. The challenge will be to identify the individual immunoprofile of each patient and the consequent choice of optimal therapy or combination of therapies to be used.

Empirical chemosensitivity testing in a spheroid model of ovarian cancer using a microfluidics-based multiplex platform.

The use of biomarkers to infer drug response in patients is being actively pursued, yet significant challenges with this approach, including the complicated interconnection of pathways, have limited its application. Direct empirical testing of tumor sensitivity would arguably provide a more reliable predictive value, although it has garnered little attention largely due to the technical difficulties associated with this approach. We hypothesize that the application of recently developed microtechnologies, coupled to more complex 3-dimensional cell cultures, could provide a model to address some of these issues. As a proof of concept, we developed a microfluidic device where spheroids of the serous epithelial ovarian cancer cell line TOV112D are entrapped and assayed for their chemoresponse to carboplatin and paclitaxel, two therapeutic agents routinely used for the treatment of ovarian cancer. In order to index the chemoresponse, we analyzed the spatiotemporal evolution of the mortality fraction, as judged by vital dyes and confocal microscopy, within spheroids subjected to different drug concentrations and treatment durations inside the microfluidic device. To reflect microenvironment effects, we tested the effect of exogenous extracellular matrix and serum supplementation during spheroid formation on their chemotherapeutic response. Spheroids displayed augmented chemoresistance in comparison to monolayer culturing. This resistance was further increased by the simultaneous presence of both extracellular matrix and high serum concentration during spheroid formation. Following exposure to chemotherapeutics, cell death profiles were not uniform throughout the spheroid. The highest cell death fraction was found at the center of the spheroid and the lowest at the periphery. Collectively, the results demonstrate the validity of the approach, and provide the basis for further investigation of chemotherapeutic responses in ovarian cancer using microfluidics technology. In the future, such microdevices could provide the framework to assay drug sensitivity in a timeframe suitable for clinical decision making.

The molecular signature of the stroma response in prostate cancer-induced osteoblastic bone metastasis highlights expansion of hematopoietic and prostate epithelial stem cell niches

The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

Survival in patients with high-risk prostate cancer is predicted by miR-221, which regulates proliferation, apoptosis, and invasion of prostate cancer cells by inhibiting IRF2 and SOCS3

A lack of reliably informative biomarkers to distinguish indolent and lethal prostate cancer is one reason this disease is overtreated. miR-221 has been suggested as a biomarker in high-risk prostate cancer, but there is insufficient evidence of its potential utility. Here we report that miR-221 is an independent predictor for cancer-related death, extending and validating earlier findings. By mechanistic investigations we showed that miR-221 regulates cell growth, invasiveness, and apoptosis in prostate cancer at least partially via STAT1/STAT3-mediated activation of the JAK/STAT signaling pathway. miR-221 directly inhibits the expression of SOCS3 and IRF2, two oncogenes that negatively regulate this signaling pathway. miR-221 expression sensitized prostate cancer cells for IFN-γ-mediated growth inhibition. Our findings suggest that miR-221 offers a novel prognostic biomarker and therapeutic target in high-risk prostate cancer.

Noninvasive Urinary Metabolomic Profiling Identifies Diagnostic and Prognostic Markers in Lung Cancer

Lung cancer remains the most common cause of cancer deaths worldwide, yet there is currently a lack of diagnostic noninvasive biomarkers that could guide treatment decisions. Small molecules (<1,500 Da) were measured in urine collected from 469 patients with lung cancer and 536 population controls using unbiased liquid chromatography/mass spectrometry. Clinical putative diagnostic and prognostic biomarkers were validated by quantitation and normalized to creatinine levels at two different time points and further confirmed in an independent sample set, which comprises 80 cases and 78 population controls, with similar demographic and clinical characteristics when compared with the training set. Creatine riboside (IUPAC name: 2-{2-[(2R,3R,4S,5R)-3,4-dihydroxy-5-(hydroxymethyl)-oxolan-2-yl]-1-methylcarbamimidamido}acetic acid), a novel molecule identified in this study, and N-acetylneuraminic acid (NANA) were each significantly (P < 0.00001) elevated in non-small cell lung cancer and associated with worse prognosis [HR = 1.81 (P = 0.0002), and 1.54 (P = 0.025), respectively]. Creatine riboside was the strongest classifier of lung cancer status in all and stage I-II cases, important for early detection, and also associated with worse prognosis in stage I-II lung cancer (HR = 1.71, P = 0.048). All measurements were highly reproducible with intraclass correlation coefficients ranging from 0.82 to 0.99. Both metabolites were significantly (P < 0.03) enriched in tumor tissue compared with adjacent nontumor tissue (N = 48), thus revealing their direct association with tumor metabolism. Creatine riboside and NANA may be robust urinary clinical metabolomic markers that are elevated in tumor tissue and associated with early lung cancer diagnosis and worse prognosis.

Bevacizumab, Pemetrexed, and Cisplatin, or Bevacizumab and Erlotinib for Patients With Advanced Non-Small-Cell Lung Cancer Stratified by Epidermal Growth Factor Receptor Mutation: Phase II Trial SAKK19/09

Treatment allocation by epidermal growth factor receptor mutation status is a new standard in patients with metastatic nonesmall-cell lung cancer. Yet, relatively few modern chemotherapy trials were conducted in patients characterized by epidermal growth factor receptor wild type. We describe the results of a multicenter phase II trial, testing in parallel 2 novel combination therapies, predefined molecular markers, and tumor rebiopsy at progression. Objective: The goal was to demonstrate that tailored therapy, according to tumor histology and epidermal growth factor receptor (EGFR) mutation status, and the introduction of novel drug combinations in the treatment of advanced nonesmall-cell lung cancer are promising for further investigation. Methods: We conducted a multicenter phase II trial with mandatory EGFR testing and 2 strata. Patients with EGFR wild type received 4 cycles of bevacizumab, pemetrexed, and cisplatin, followed by maintenance with bevacizumab and pemetrexed until progression. Patients with EGFR mutations received bevacizumab and erlotinib until progression. Patients had computed tomography scans every 6 weeks and repeat biopsy at progression. The primary end point was progression-free survival (PFS) ≥ 35% at 6 months in stratum EGFR wild type; 77 patients were required to reach a power of 90% with an alpha of 5%. Secondary end points were median PFS, overall survival, best overall response rate (ORR), and tolerability. Further biomarkers and biopsy at progression were also evaluated. Results: A total of 77 evaluable patients with EGFR wild type received an average of 9 cycles (range, 1-25). PFS at 6 months was 45.5%, median PFS was 6.9 months, overall survival was 12.1 months, and ORR was 62%. Kirsten rat sarcoma oncogene mutations and circulating vascular endothelial growth factor negatively correlated with survival, but thymidylate synthase expression did not. A total of 20 patients with EGFR mutations received an average of 16.

Spatial genomic heterogeneity within localized, multifocal prostate cancer

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Tumor infiltrating lymphocytes in ovarian cancer.

Several improvements in ovarian cancer treatment have been achieved in recent years, both in surgery and in combination chemotherapy with targeting. However, ovarian tumors remain the women's cancers with highest mortality rates. In this scenario, a pivotal role has been endorsed to the immunological environment and to the immunological mechanisms involved in ovarian cancer behavior. Recent evidence suggests a loss of the critical balance between immune-activating and immune-suppressing mechanisms when oncogenesis and cancer progression occur. Ovarian cancer generates a mechanism to escape the immune system by producing a highly suppressive environment. Immune-activated tumor infiltrating lymphocytes (TILs) in ovarian tumor tissue testify that the immune system is the trigger in this neoplasm. The TIL mileau has been demonstrated to be associated with better prognosis, more chemosensitivity, and more cases of optimal residual tumor achieved during primary cytoreduction. Nowadays, scientists are focusing attention on new immunologically effective tumor biomarkers in order to optimize selection of patients for recruitment in clinical trials and to identify relationships of these biomarkers with responses to immunotherapeutics. Assessing this point of view, TILs might be considered as a potent predictive immunotherapy biomarker.