Association between tumour infiltrating lymphocytes, histotype and clinical outcome in epithelial ovarian cancer.

BACKGROUND: There is evidence that some ovarian tumours evoke an immune response, which can be assessed by tumour infiltrating lymphocytes (TILs). To facilitate adoption of TILs as a clinical biomarker, a standardised method for their H&E visual evaluation has been validated in breast cancer. METHODS: We sought to investigate the prognostic significance of TILs in a study of 953 invasive epithelial ovarian cancer tumour samples, both primary and metastatic, from 707 patients from the prospective population-based SEARCH study. TILs were analysed using a standardised method based on H&E staining producing a percentage score for stromal and intratumoral compartments. We used Cox regression to estimate hazard ratios of the association between TILs and survival. RESULTS: The extent of stromal and intra-tumoral TILs were correlated in the primary tumours (n = 679, Spearman's rank correlation = 0.60, P < 0.001) with a similar correlation in secondary tumours (n = 224, Spearman's rank correlation = 0.62, P < 0.001). There was a weak correlation between stromal TIL levels in primary and secondary tumour samples (Spearman's rank correlation = 0.29, P < 0.001) and intra-tumoral TIL levels in primary and secondary tumour samples (Spearman's rank correlation = 0.19, P = 0.0094). The extent of stromal TILs differed between histotypes (Pearson chi2 (12d.f.) 54.1, P < 0.0001) with higher levels of stromal infiltration in the high-grade serous and endometriod cases. A significant association was observed for higher intratumoral TIL levels and a favourable prognosis (HR 0.74 95% CI 0.55-1.00 p = 0.047). CONCLUSION: This study is the largest collection of epithelial ovarian tumour samples evaluated for TILs. We have shown that stromal and intratumoral TIL levels are correlated and that their levels correlate with clinical variables such as tumour histological subtype. We have also shown that increased levels of both intratumoral and stromal TILs are associated with a better prognosis; however, this is only statistically significant for intratumoral TILs. This study suggests that a clinically useful immune prognostic indicator in epithelial ovarian cancer could be developed using this technique

Germline whole exome sequencing and large-scale replication identifies FANCM as a likely high grade serous ovarian cancer susceptibility gene.

We analyzed whole exome sequencing data in germline DNA from 412 high grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas Project and identified 5,517 genes harboring a predicted deleterious germline coding mutation in at least one HGSOC case. Gene-set enrichment analysis showed enrichment for genes involved in DNA repair (p = 1.8×10-3). Twelve DNA repair genes - APEX1, APLF, ATX, EME1, FANCL, FANCM, MAD2L2, PARP2, PARP3, POLN, RAD54L and SMUG1 - were prioritized for targeted sequencing in up to 3,107 HGSOC cases, 1,491 cases of other epithelial ovarian cancer (EOC) subtypes and 3,368 unaffected controls of European origin. We estimated mutation prevalence for each gene and tested for associations with disease risk. Mutations were identified in both cases and controls in all genes except MAD2L2, where we found no evidence of mutations in controls. In FANCM we observed a higher mutation frequency in HGSOC cases compared to controls (29/3,107 cases, 0.96 percent; 13/3,368 controls, 0.38 percent; P=0.008) with little evidence for association with other subtypes (6/1,491, 0.40 percent; P=0.82). The relative risk of HGSOC associated with deleterious FANCM mutations was estimated to be 2.5 (95% CI 1.3 - 5.0; P=0.006). In summary, whole exome sequencing of EOC cases with large-scale replication in case-control studies has identified FANCM as a likely novel susceptibility gene for HGSOC, with mutations associated with a moderate increase in risk. These data may have clinical implications for risk prediction and prevention approaches for high-grade serous ovarian cancer in the future and a significant impact on reducing disease mortality

Higher incidence of premenopausal breast cancer in less developed countries; myth or truth?

Background: Fundamental etiologic differences have been suggested to cause earlier onset of breast cancer in less developed countries (LDCs) than in more developed countries (MDCs). We explored this hypothesis using world-wide breast cancer incidence data. Methods: We compared international age-standardized incidence rates (ASR) of pre- (<50 years) and postmenopausal (≥50 years) breast cancers as well as temporal trends in ASRs of pre-and postmenopausal breast cancer among selected countries during 1975–2008. We used joinpoint log-linear regression analysis to estimate annual percent changes (APC) for premenopausal and postmenopausal breast cancer in the northern Europe and in Black and White women population in the US. Results: Premenopausal breast cancers comprised a substantially higher proportion of all incident breast cancers in LDCs (average 47.3%) compared to MDCs (average 18.5%). However, the ASR of premenopausal breast cancer was consistently higher in MDCs (29.4/100,000) than LDCs (12.8/100,000). The ASR of postmenopausal cancer was about five-fold higher in the MDCs (307.6/100,000) than the LDCs (65.4/100,000). The APC of breast cancer in Denmark was substantially higher in postmenopausal (1.33%) than premenopausal cancer (0.98%). Higher incidence of breast cancer among the white than black women in the US was pertained only to the postmenopausal cancer. Conclusion: The substantial and consistent lower age-specific incidence of breast cancer in LDCs than in MDCs contradicts the theory of earlier onset. Demographic differences with fewer old women in LDCs and lower prevalence of risk factors of postmenopausal cancer are the most likely explanation to the lower mean age at diagnosis in these countries

Computational pathology of pre-treatment biopsies identifies lymphocyte density as a predictor of response to neoadjuvant chemotherapy in breast cancer.

BACKGROUND: There is a need to improve prediction of response to chemotherapy in breast cancer in order to improve clinical management and this may be achieved by harnessing computational metrics of tissue pathology. We investigated the association between quantitative image metrics derived from computational analysis of digital pathology slides and response to chemotherapy in women with breast cancer who received neoadjuvant chemotherapy. METHODS: We digitised tissue sections of both diagnostic and surgical samples of breast tumours from 768 patients enrolled in the Neo-tAnGo randomized controlled trial. We subjected digital images to systematic analysis optimised for detection of single cells. Machine-learning methods were used to classify cells as cancer, stromal or lymphocyte and we computed estimates of absolute numbers, relative fractions and cell densities using these data. Pathological complete response (pCR), a histological indicator of chemotherapy response, was the primary endpoint. Fifteen image metrics were tested for their association with pCR using univariate and multivariate logistic regression. RESULTS: Median lymphocyte density proved most strongly associated with pCR on univariate analysis (OR 4.46, 95 % CI 2.34-8.50, p < 0.0001; observations = 614) and on multivariate analysis (OR 2.42, 95 % CI 1.08-5.40, p = 0.03; observations = 406) after adjustment for clinical factors. Further exploratory analyses revealed that in approximately one quarter of cases there was an increase in lymphocyte density in the tumour removed at surgery compared to diagnostic biopsies. A reduction in lymphocyte density at surgery was strongly associated with pCR (OR 0.28, 95 % CI 0.17-0.47, p < 0.0001; observations = 553). CONCLUSIONS: A data-driven analysis of computational pathology reveals lymphocyte density as an independent predictor of pCR. Paradoxically an increase in lymphocyte density, following exposure to chemotherapy, is associated with a lack of pCR. Computational pathology can provide objective, quantitative and reproducible tissue metrics and represents a viable means of outcome prediction in breast cancer. TRIAL REGISTRATION: ClinicalTrials.gov NCT00070278 ; 03/10/2003.We acknowledge funding from Cancer Research UK and NIHR Cambridge Biomedical Research Centre. HRA is an NIHR Academic Clinical Lecturer supported by a Career Development Fellowship from the Pathological Society of Great Britain and Northern Ireland and a Starter Grant for Clinical Lecturers from the Academy of Medical Sciences.This is the final version of the article. It first appeared from BioMed Central via https://doi.org 10.1186/s13058-016-0682-

Refined cut-off for TP53 immunohistochemistry improves prediction of TP53 mutation status in ovarian mucinous tumors: implications for outcome analyses.

TP53 mutations are implicated in the progression of mucinous borderline tumors (MBOT) to mucinous ovarian carcinomas (MOC). Optimized immunohistochemistry (IHC) for TP53 has been established as a proxy for the TP53 mutation status in other ovarian tumor types. We aimed to confirm the ability of TP53 IHC to predict TP53 mutation status in ovarian mucinous tumors and to evaluate the association of TP53 mutation status with survival among patients with MBOT and MOC. Tumor tissue from an initial cohort of 113 women with MBOT/MOC was stained with optimized IHC for TP53 using tissue microarrays (75.2%) or full sections (24.8%) and interpreted using established criteria as normal or abnormal (overexpression, complete absence, or cytoplasmic). Cases were considered concordant if abnormal IHC staining predicted deleterious TP53 mutations. Discordant tissue microarray cases were re-evaluated on full sections and interpretational criteria were refined. The initial cohort was expanded to a total of 165 MBOT and 424 MOC for the examination of the association of survival with TP53 mutation status, assessed either by TP53 IHC and/or sequencing. Initially, 82/113 (72.6%) cases were concordant using the established criteria. Refined criteria for overexpression to account for intratumoral heterogeneity and terminal differentiation improved concordance to 93.8% (106/113). In the expanded cohort, 19.4% (32/165) of MBOT showed evidence for TP53 mutation and this was associated with a higher risk of recurrence, disease-specific death, and all-cause mortality (overall survival: HR = 4.6, 95% CI 1.5-14.3, p = 0.0087). Within MOC, 61.1% (259/424) harbored a TP53 mutation, but this was not associated with survival (overall survival, p = 0.77). TP53 IHC is an accurate proxy for TP53 mutation status with refined interpretation criteria accounting for intratumoral heterogeneity and terminal differentiation in ovarian mucinous tumors. TP53 mutation status is an important biomarker to identify MBOT with a higher risk of mortality.KLG is supported by the Victorian Cancer Agency (MCRF15013) and the Australian National Health and Medical Research Council (APP1045783 and #628434). This study was supported by the Peter MacCallum Cancer Foundation. CS is supported by a University of Melbourne Postgraduate Scholarship. DDB is supported by National Health and Medical Research Council of Australia (NHMRC) grants APP1092856 and APP1117044 and by the US National Cancer Institute U54 programme (U54CA209978-04). ELG and SHK are supported through P50 CA136393-10. The following cohorts that contributed to the GAMuT study were supported as follows: CASCADE: Supported by the Peter MacCallum Cancer Foundation AOCS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, The Cancer Council Victoria, Queensland Cancer Fund, The Cancer Council New South Wales, The Cancer Council South Australia, The Cancer Council Tasmania and The Cancer Foundation of Western Australia (Multi-State Applications 191, 211 and 182) and the National Health and Medical Research Council of Australia (NHMRC; ID400413 and ID400281). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation. The AOCS also acknowledges the cooperation of the participating institutions in Australia and acknowledges the contribution of the study nurses, research assistants and all clinical and scientific collaborators to the study. The complete AOCS Study Group can be found at www.aocstudy.org. We would like to thank all of the women who participated in these research programs. OVCARE receives core funding from The BC Cancer Foundation and the VGH and UBC Hospital Foundation. The Gynaecological Oncology Biobank at Westmead is a member of the Australasian Biospecimen Network-Oncology group, which was funded by the National Health and Medical Research Council Enabling Grants ID 310670 & ID 628903 and the Cancer Institute NSW Grants ID 12/RIG/1-17 & 15/RIG/1-16. COEUR: This study uses resources provided by the Canadian Ovarian Cancer Research Consortium’s - COEUR biobank funded by the Terry Fox Research Institute and managed and supervised by the Centre hospitalier de l’Université de Montréal (CRCHUM). The Consortium acknowledges contributions to its COEUR biobank from Institutions across Canada (for a full list see http://www.tfri.ca/en/research/translational-research/coeur/coeur_biobanks.aspx). The following cohorts that contributed to OTTA were supported as follows: AOV: Canadian Institutes of Health Research (MOP-86727), Cancer Research Society (19319). BAV: ELAN Funds of the University of Erlangen-Nuremberg; DOV: NCI/NIH R01CA168758. Huntsman Cancer Foundation and the National Cancer Institute of the National Institutes of Health under Award Number P30CA042014. HAW: U.S. National 19 Institutes of Health (R01-CA58598, N01-CN-55424 and N01-PC-67001); MAY: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; SEA: SEARCH team: Mitul Shah, Jennifer Alsopp, Mercedes Jiminez-Linan SEARCH funding: Cancer Research UK (C490/A16561), the Cancer Research UK Cambridge Cancer Centre and the National Institute for Health Research Cambridge Biomedical Research Centres. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. JBD: Cancer Research UK Institute Group Award UK A22905 and A15601; STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and årKampMotCancer foundation; TVA: Canadian Institutes of Health Research grant (MOP-86727) and NIH/NCI 1 R01CA160669- 01A1; VAN: M.S. Anglesio is funded through a Michael Smith Foundation for Health Research Scholar Award and the Janet D. Cottrelle Foundation Scholars program managed by the BC Cancer Foundation. The Vancouver study cohort (TVAN) is supported by BC’s Ovarian Cancer Research team (OVCARE), the BC Cancer Foundation and The VGH+UBC Hospital Foundation. WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16

Chemical and biomechanical characterization of hyperhomocysteinemic bone disease in an animal model

BACKGROUND: Classical homocystinuria is an autosomal recessive disorder caused by cystathionine β-synthase (CBS) deficiency and characterized by distinctive alterations of bone growth and skeletal development. Skeletal changes include a reduction in bone density, making it a potentially attractive model for the study of idiopathic osteoporosis. METHODS: To investigate this aspect of hyperhomocysteinemia, we supplemented developing chicks (n = 8) with 0.6% dl-homocysteine (hCySH) for the first 8 weeks of life in comparison to controls (n = 10), and studied biochemical, biomechanical and morphologic effects of this nutritional intervention. RESULTS: hCySH-fed animals grew faster and had longer tibiae at the end of the study. Plasma levels of hCySH, methionine, cystathionine, and inorganic sulfate were higher, but calcium, phosphate, and other indices of osteoblast metabolism were not different. Radiographs of the lower limbs showed generalized osteopenia and accelerated epiphyseal ossification with distinct metaphyseal and suprametaphyseal lucencies similar to those found in human homocystinurics. Although biomechanical testing of the tibiae, including maximal load to failure and bone stiffness, indicated stronger bone, strength was proportional to the increased length and cortical thickness in the hCySH-supplemented group. Bone ash weights and IR-spectroscopy of cortical bone showed no difference in mineral content, but there were higher Ca(2+)/PO(4)(3- )and lower Ca(2+)/CO(3)(2- )molar ratios than in controls. Mineral crystallization was unchanged. CONCLUSION: In this chick model, hyperhomocysteinemia causes greater radial and longitudinal bone growth, despite normal indices of bone formation. Although there is also evidence for an abnormal matrix and altered bone composition, our finding of normal biomechanical bone strength, once corrected for altered morphometry, suggests that any increase in the risk of long bone fracture in human hyperhomocysteinemic disease is small. We also conclude that the hCySH-supplemented chick is a promising model for study of the connective tissue abnormalities associated with homocystinuria and an important alternative model to the CBS knock-out mouse

A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer.

Complex focal chromosomal rearrangements in cancer genomes, also called "firestorms", can be scored from DNA copy number data. The complex arm-wise aberration index (CAAI) is a score that captures DNA copy number alterations that appear as focal complex events in tumors, and has potential prognostic value in breast cancer. This study aimed to validate this DNA-based prognostic index in breast cancer and test for the first time its potential prognostic value in ovarian cancer. Copy number alteration (CNA) data from 1950 breast carcinomas (METABRIC cohort) and 508 high-grade serous ovarian carcinomas (TCGA dataset) were analyzed. Cases were classified as CAAI positive if at least one complex focal event was scored. Complex alterations were frequently localized on chromosome 8p (n = 159), 17q (n = 176) and 11q (n = 251). CAAI events on 11q were most frequent in estrogen receptor positive (ER+) cases and on 17q in estrogen receptor negative (ER-) cases. We found only a modest correlation between CAAI and the overall rate of genomic instability (GII) and number of breakpoints (r = 0.27 and r = 0.42, p < 0.001). Breast cancer specific survival (BCSS), overall survival (OS) and ovarian cancer progression free survival (PFS) were used as clinical end points in Cox proportional hazard model survival analyses. CAAI positive breast cancers (43%) had higher mortality: hazard ratio (HR) of 1.94 (95%CI, 1.62-2.32) for BCSS, and of 1.49 (95%CI, 1.30-1.71) for OS. Representations of the 70-gene and the 21-gene predictors were compared with CAAI in multivariable models and CAAI was independently significant with a Cox adjusted HR of 1.56 (95%CI, 1.23-1.99) for ER+ and 1.55 (95%CI, 1.11-2.18) for ER- disease. None of the expression-based predictors were prognostic in the ER- subset. We found that a model including CAAI and the two expression-based prognostic signatures outperformed a model including the 21-gene and 70-gene signatures but excluding CAAI. Inclusion of CAAI in the clinical prognostication tool PREDICT significantly improved its performance. CAAI positive ovarian cancers (52%) also had worse prognosis: HRs of 1.3 (95%CI, 1.1-1.7) for PFS and 1.3 (95%CI, 1.1-1.6) for OS. This study validates CAAI as an independent predictor of survival in both ER+ and ER- breast cancer and reveals a significant prognostic value for CAAI in high-grade serous ovarian cancer

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention

A transcriptome-wide association study among 97,898 women to identify candidate susceptibility genes for epithelial ovarian cancer risk

Large-scale genome-wide association studies (GWAS) have identified approximately 35 loci associated with epithelial ovarian cancer (EOC) risk. The majority of GWAS-identified disease susceptibility variants are located in non-coding regions, and causal genes underlying these associations remain largely unknown. Here we performed a transcriptome-wide association study to search for novel genetic loci and plausible causal genes at known GWAS loci. We used RNA sequencing data (68 normal ovarian-tissue samples from 68 individuals and 6,124 cross-tissue samples from 369 individuals) and high-density genotyping data from European descendants of the Genotype-Tissue Expression (GTEx V6) project to build ovarian and cross-tissue models of genetically regulated expression using elastic net methods. We evaluated 17,121 genes for their cis-predicted gene expression in relation to EOC risk using summary statistics data from GWAS of 97,898 women, including 29,396 EOC cases. With a Bonferroni-corrected significance level of P<2.2×10-6, we identified 35 genes including FZD4 at 11q14.2 (Z=5.08, P=3.83×10-7, the cross-tissue model; 1 Mb away from any GWAS-identified EOC risk variant), a potential novel locus for EOC risk. All other 34 significantly-associated genes were located within 1 Mb of known GWAS-identified loci, including 23 genes at 6 loci not previously linked to EOC risk. Upon conditioning on nearby known EOC GWAS-identified variants, the associations for 31 genes disappeared and 3 genes remained (P<1.47 x 10-3). These data identify one novel locus (FZD4) and 34 genes at 13 known EOC risk loci associated with EOC risk, providing new insights into EOC carcinogenesis