Precision treatment for cancer: Role of prognostic and predictive markers

Tumor grade-titude: XGBoost radiomics paves the way for RCC classification

This study aimed to develop and evaluate a non-invasive XGBoost-based machine learning model using radiomic features extracted from pre-treatment CT images to differentiate grade 4 renal cell carcinoma (RCC) from lower-grade tumours. A total of 102 RCC patients who underwent contrast-enhanced CT scans were included in the analysis. Radiomic features were extracted, and a two-step feature selection methodology was applied to identify the most relevant features for classification. The XGBoost model demonstrated high performance in both training (AUC = 0.87) and testing (AUC = 0.92) sets, with no significant difference between the two (p = 0.521). The model also exhibited high sensitivity, specificity, positive predictive value, and negative predictive value. The selected radiomic features captured both the distribution of intensity values and spatial relationships, which may provide valuable insights for personalized treatment decision-making. Our findings suggest that the XGBoost model has the potential to be integrated into clinical workflows to facilitate personalized adjuvant immunotherapy decision-making, ultimately improving patient outcomes. Further research is needed to validate the model in larger, multicentre cohorts and explore the potential of combining radiomic features with other clinical and molecular data.

Differential Serum Peptidomics Reveal Multi-Marker Models That Predict Breast Cancer Progression

Here, we assess how the differential expression of low molecular weight serum peptides might predict breast cancer progression with high confidence. We apply an LC/MS-MS-based, unbiased 'omics' analysis of serum samples from breast cancer patients to identify molecules that are differentially expressed in stage I and III breast cancer. Results were generated using standard and machine learning-based analytical workflows. With standard workflow, a discovery study yielded 65 circulating biomarker candidates with statistically significant differential expression. A second study confirmed the differential expression of a subset of these markers. Models based on combinations of multiple biomarkers were generated using an exploratory algorithm designed to generate greater diagnostic power and accuracy than any individual markers. Individual biomarkers and the more complex multi-marker models were then tested in a blinded validation study. The multi-marker models retained their predictive power in the validation study, the best of which attained an AUC of 0.84, with a sensitivity of 43% and a specificity of 88%. One of the markers with m/z 761.38, which was downregulated, was identified as a fibrinogen alpha chain. Machine learning-based analysis yielded a classifier that correctly categorizes every subject in the study and demonstrates parameter constraints required for high confidence in classifier output. These results suggest that serum peptide biomarker models could be optimized to assess breast cancer stage in a clinical setting.

Clinical outcomes and prognostic factors of head and neck squamous cell carcinoma: a ten-year follow-up study

Traditional guidelines for determining the prognosis of patients with head and neck squamous cell carcinoma (HNSCC) are used to make therapeutic decisions. However, only 50% of the patients had lived for more than five years. The present study aimed to analyze the correlation of traditional prognostic factors such as tumor size, histological grading, regional metastases, and treatment with the survival of patients with HNSCC. A total of 78 patients diagnosed with HNSCC were followed up for 10 years after diagnosis and treatment. The health status of the patients was tracked at four time points, and according to the evolution of the patients and their final clinical status, we performed a prognostic analysis based on the clinical outcomes observed during the follow-up period. The final study cohort comprised 50 patients. Most patients had tumors < 4 cm in size (64%) and no regional metastases (64%); no patients had distant metastases at the time of diagnosis. Most individuals had tumors with good (48%) and moderate (46%) degrees of malignancy. At the end of the follow-up period, only 14% of the patients were discharged, 42% died of the tumor, and 44% remained under observation owing to the presence of a potentially malignant disorder, relapse, or metastases. This analysis showed that traditional prognostic factors were not accurate in detecting subclinical changes or predicting the clinical evolution of patients.

Exploring the challenges of and solutions to sharing personal genomic data for use in healthcare

Boosted by the COVID-19 pandemic, as well as the tightened General Data Protection Regulation (GDPR) legislation within the European Union (EU), individuals have become increasingly concerned about privacy. This is also reflected in how willing individuals are to consent to sharing personal data, including their health data. To understand this behaviour better, this study focuses on willingness to consent in relation to genomic data. The study explores how the provision of educational information relates to willingness to consent, as well as differences in privacy concerns, information sensitivity and the perceived trade-off value between individuals willing versus unwilling to consent to sharing their genomic data. Of the respondents, 65% were initially willing to consent, but after educational information 89% were willing to consent and only 11% remained unwilling to consent. Educating individuals about potential health benefits can thus help to correct the beliefs that originally led to the unwillingness to share genomic data.

Pretreatment Squamous Cell Carcinoma Antigen (SCC-Ag) as a Predictive Factor for the Use of Consolidation Chemotherapy in Cervical Cancer Patients After Postoperative Extended-Field Concurrent Chemoradiotherapy

Objective: The goal of this study was to confirm the clinical value of pretreatment serum squamous cell carcinoma antigen (SCC-Ag) in the administration of consolidation chemotherapy in patients with cervical cancers undergoing postoperative extended-field radiotherapy (EFRT) and concurrent chemotherapy (CCRT). Methods: Between 2007 and 2018, a total of 113 patients were treated with postoperative extended-field intensity-modulated radiotherapy (EF-IMRT) and CCRT. There were 63 patients receiving extended-field concurrent chemoradiotherapy (EF-CCRT) and consolidation chemotherapy, while another 50 patients underwent EF-CCRT alone. For the planning target volume, the prescribed dose was 45 to 50.4Gy/25 to 28 fractions. The consolidation chemotherapy regimen contained docetaxel and cisplatin. Results: For the patients with high pretreatment SCC-Ag, the addition of consolidation chemotherapy significantly improved their treatment outcomes and they had better 5-year overall survival (OS) (81.02% vs 63.44%, P = .018) and disease-free survival (DFS) (76.95% vs 61.12%, P = .007) than those without it. Meanwhile, the patients with consolidation chemotherapy had a lower rate of distant metastasis (8.8% vs 34.8%, P = .001). For the patients with low pretreatment SCC-Ag, there was no difference in prognosis between patients receiving consolidation chemotherapy and those not receiving consolidation. In multivariate analysis, consolidation chemotherapy was found to be a factor significantly associated with DFS (P = .035, 95% confidence interval (CI): 0.304-0.977) and distant metastasis (P = .009, 95% CI: 0.125-0.841). Conclusion: The patients who received consolidation chemotherapy showed significantly better DFS. Furthermore, pretreatment serum SCC-Ag > 6.5 ng/mL may be a predictive factor for the use of consolidation chemotherapy in cervical cancer patients treated with postoperative EF-CCRT.

Inexpensive Systemic Inflammatory Biomarkers in Ovarian Cancer: An Umbrella Systematic Review of 17 Prognostic Meta-Analyses

The association of several inflammation-based biomarkers [lymphocyte-to-monocyte, neutrophil-to-lymphocyte, and platelet-to-lymphocyte ratios (LMR, NLR, and PLR, respectively)] with the survival of epithelial ovarian cancer (EOC) patients has been extensively investigated in several systematic reviews and meta-analyses (MAs) of observational studies. The aim of this umbrella systematic review is to appraise all available results in published MAs that explored the association between these biomarkers and EOC outcomes. An umbrella systematic review of the current evidence for systemic inflammatory biomarkers in the peripheral blood of EOC patients was performed by searching several databases including PubMed/Medline and Web of Science. The quality of the MAs was appraised using the AMSTAR-2 tool as well as other qualitative criteria. The evidence was graded from convincing (Class I) to weak (Class IV). Our umbrella review appraised 17 MAs of retrospective studies (range: 7-16) with a number of enrolled patients ranging from 1,636 to 4,910 patients in each MA. All these MAs demonstrated that pretreatment high NLR and PLR, as well as low LMR, were independent predictors of poor overall survival and progression-free survival in EOC. Nearly all published MAs were conducted by Chinese researchers (16/17) and were redundant in their character. Another issue in these MAs is the absence of prior PROSPERO database registration as well as the earlier exclusion of the gray literature. On the other hand, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses Of Observational Studies in Epidemiology (MOOSE)-based reporting guidelines were used in nine out of the 17 MAs. A good number of MAs have transparently provided funding acknowledgment. The AMSTAR-2-based assessment showed low quality in 11 out of the 17 reviewed MAs. This negative rating was largely due to the absence of critical domains. Finally, all evaluated MAs were rated as Class III or IV (suggestive and weak, respectively). Despite the power of MAs in increasing sampling and precision, the quality of the current non-randomized evidence on this topic is still weak.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, identifier CRD42020201493.

Targeting p53 for the treatment of cancer

Dysfunction of the TP53 (p53) gene occurs in most if not all human malignancies. Two principal mechanisms are responsible for this dysfunction; mutation and downregulation of wild-type p53 mediated by MDM2/MDM4. Because of its almost universal inactivation in malignancy, p53 is a highly attractive target for the development of new anticancer drugs. Although multiple strategies have been investigated for targeting dysfunctional p53 for cancer treatment, only 2 of these have so far yielded compounds for testing in clinical trials. These strategies include the identification of compounds for reactivating the mutant form of p53 back to its wild-type form and compounds for inhibiting the interaction between wild-type p53 and MDM2/MDM4. Currently, multiple p53-MDM2/MDM4 antagonists are undergoing clinical trials, the most advanced being idasanutlin which is currently undergoing testing in a phase III clinical trial in patients with relapsed or refractory acute myeloid leukemia. Two mutant p53-reactivating compounds have progressed to clinical trials, i.e., APR-246 and COTI-2. Although promising data has emerged from the testing of both MDM2/MDM4 inhibitors and mutant p53 reactivating compounds in preclinical models, it is still unclear if these agents have clinical efficacy. However, should any of the compounds currently being evaluated in clinical trials be shown to have efficacy, it is likely to usher in a new era in cancer treatment, especially as p53 dysfunction is so prevalent in human cancers.

Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

Background

After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10–30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives.

Objective

To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml^− 1) and tumour volume, can be used for early prediction of pathologic response.

Methods

One hunred four women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3–6. The cell-loss metric was established at baseline (n = 104), 48 h after cycle 2 (n = 104) and prior to cycle 2 (n = 57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later.

Results

Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48 h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11, 11, 23 and 46%) differed significantly (p = 0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p = 0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8 and 83.3%, compared to 40.5 and 88.7% 48 h after treatment 2.

Conclusion

A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

Trial registration

PROMIX (Clinical Trials.govNCT000957125).

Early prediction of pathologic response to neoadjuvant treatment of breast cancer: use of a cell-loss metric based on serum thymidine kinase 1 and tumour volume

BACKGROUND

After neoadjuvant chemotherapy of breast cancer pathologic complete response (pCR) indicates a favorable prognosis. Among non-selected patients, pCR is, however, achieved in only 10-30%. Early evaluation of tumour response to treatment would facilitate individualized therapy, with ineffective chemotherapy interrupted or changed. The methodology for this purpose is still limited. Tumour imaging and analysis of macromolecules, released from disrupted tumour cells, are principal alternatives.

OBJECTIVE

To investigate whether a metric of cell-loss, defined as the ratio between serum concentration of thymidine kinase1 (sTK1, ng x ml^- 1) and tumour volume, can be used for early prediction of pathologic response.

METHODS

One hunred four women with localized breast cancer received neoadjuvant epirubicin/docetaxel in 6 cycles, supplemented with bevacizumab in cycles 3-6. The cell-loss metric was established at baseline (n = 104), 48 h after cycle 2 (n = 104) and prior to cycle 2 (n = 57). The performance of the metric was evaluated by association with pathologic tumour response at surgery 4 months later.

RESULTS

Treatment caused a rise in sTK1, a reduction in tumour volume and a marked increase in the cell-loss metric. Patients were subdivided into quartiles according to the baseline cell-loss metric. For these groups, baseline means were 0.0016, 0.0042, 0.0062, 0.0178 units. After subtraction of baselines, means for the quartiles 48 h after treatment 2 were 0.002, 0.011, 0.030 and 0.357 units. pCR was achieved in 24/104, their distribution in the quartiles (11, 11, 23 and 46%) differed significantly (p = 0.01). In 80 patients with remaining tumour, tumour size was inversely related to the metric (p = 0.002). In 57 patients studied before treatment 2, positive and negative predictive values of the metric were 77.8 and 83.3%, compared to 40.5 and 88.7% 48 h after treatment 2.

CONCLUSION

A cell-loss metric, based on serum levels of TK1, released from disrupted tumour cells, and tumour volume, reveal tumour response early during neoadjuvant treatment. The metric reflect tumour properties that differ greatly between patients and determine the sensitivity to cytotoxic treatment. The findings point to the significance of cell loss for tumour growth rate. The metric should be considered in personalized oncology and in the evaluation of new therapeutic modalities.

TRIAL REGISTRATION

PROMIX (Clinical Trials.govNCT000957125).

Clinical Evaluation of a New Point-of-Care System for Chemistry Panel Testing

Background

GEM Premier ChemSTAT™ is a point-of-care (POC) system that measures Na+, K+, Ca++, Cl−, glucose, hematocrit, creatinine, blood urea nitrogen (BUN), tCO2, pH, pCO2, and lactate from a single whole blood specimen, providing rapid results in POC settings such as the emergency department (ED). Accurate measurements of creatinine in whole blood and reporting of estimated glomerular filtration rate (eGFR) can minimize adverse effects of contrast-induced nephropathy.

Methods

Heparinized whole blood specimens from the ED were analyzed on the ChemSTAT by POC staff. Method comparison was performed against the cobas Integra c501 for creatinine, BUN, and tCO2, and against the GEM Premier 4000 for all other analytes. Precision was conducted with whole blood specimens assayed in triplicate over 6 days. Creatinine results from whole blood and plasma were used for eGFR, by isotope dilution mass spectrometry-traceable Modification of Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration equations, and eGFR concordance was assessed.

Results

Creatinine, BUN, and tCO2 correlated well with plasma samples on the cobas, and all other analytes correlated well with whole blood specimens on the GEM Premier 4000 across the tested sample ranges. The regression slope was 0.951 to 1.047, along with a correlation coefficient (r) of ≥0.982 for all analytes. The pooled within-sample precision was 0% to 2.5% for all analytes.

Conclusions

ChemSTAT demonstrated a strong correlation with the comparative methods and excellent precision. The system's analytical performance and continuous quality management make it suitable for use in the ED to provide rapid reliable test results, which could minimize the time to treatment and improve ED efficiency.

Circulating tumour DNA as a cancer biomarker

Measurement of genetically altered DNA shed from tumours into the circulation can potentially provide a new generation of blood-based cancer biomarkers. Compared with tissue DNA biomarkers which require surgery or biopsy, samples for circulating tumour DNA assays can be obtained with minimal inconvenience and at lower cost. Furthermore, in contrast to tissue, the use of circulating tumour DNA allows serial monitoring, faster delivery of results and potentially provides an integrative representation of genetic alterations across all tumour sites within a patient. In contrast to existing protein-based cancer biomarkers, all of which can be produced by benign disease, circulating tumour DNA biomarkers would be expected to be more specific for malignancy. Furthermore, unlike the available blood cancer biomarkers, circulating tumour DNA can be used to predict response to specific therapies, identify mechanisms of therapy resistance and detect potentially actionable mutations. One of the first circulating tumour DNA assays recommended for clinical use involves EGFR mutation testing for predicting response to EGFR tyrosine kinase inhibitors in patients with advanced non-small cell lung cancer, especially when tumour tissue is unavailable. In order to accelerate the introduction of circulating tumour DNA assays into routine clinical use, laboratory medicine staff will have to undergo training in the use of polymerase chain reaction and DNA sequencing. Furthermore, existing circulating tumour DNA assays will need to be simplified, standardized, shown to have clinical utility, be made available at reasonable costs and be reimbursable.

Prediction of therapy response in ovarian cancer: Where are we now?

Therapy resistance is a major challenge in the management of ovarian cancer (OC). Advances in detection and new technology validation have led to the emergence of biomarkers that can predict responses to available therapies. It is important to identify predictive biomarkers to select resistant and sensitive patients in order to reduce important toxicities, to reduce costs and to increase survival. The discovery of predictive and prognostic biomarkers for monitoring therapy is a developing field and provides promising perspectives in the era of personalized medicine. This review article will discuss the biology of OC with a focus on targetable pathways; current therapies; mechanisms of resistance; predictive biomarkers for chemotherapy, antiangiogenic and DNA-targeted therapies, and optimal cytoreductive surgery; and the emergence of liquid biopsy using recent studies from the Medline database and ClinicalTrials.gov.

The assessment of the prognostic value of tumor markers and cytokines as SCCAg, CYFRA 21.1, IL-6, VEGF and sTNF receptors in patients with squamous cell cervical cancer, particularly with early stage of the disease

The aim of this study is to determine the prognostic value of tumor markers, as squamous cell carcinoma antigen (SCCAg) and cytokeratin-19 fragment (CYFRA 21.1) and interleukin 6 (IL-6), vascular endothelial growth factor (VEGF), soluble tumor necrosis factor receptor I (sTNF RI), and sTNF RII in patients with squamous cell carcinoma of the cervix. The subjects of analysis were 138 patients with stage I–IVA according to the International Federation of Gynecology and Obstetrics (FIGO) classification. The collected research material comes from one oncology center. During the 10 years of follow-up, 56 relapses and 53 deaths were observed, and recurrent disease in early stage was confirmed in 45 % of patients. The pretreatment serum levels of SCCAg and CYFRA 21.1, and cytokines IL-6, VEGF, sTNF RI, and sTNF RII were determined in all patients. The probability of disease-free survival (DFS) and overall survival (OS) was evaluated using the log-rank test and the Cox regression model. Based on the ROC curve analysis for patients with recurrence, the largest area under the curve was demonstrated for SCCAg and IL-6 and for patients who died, for SCCAg and VEGF. Cox analysis demonstrated that independent prognostic factor for DFS was only SCCAg and for OS cytokine IL-6 and SCCAg, but in patients with early stage the prognostic value for DFS was VEGF, whereas IL-6 and CYFRA 21.1 for OS. Serum level of VEGF, CYFRA 21.1 and IL-6 before treatment in patients with early stage cervical cancer appears to be an important prognostic factor.

Retracing Circulating Tumour Cells for Biomarker Characterization after Enumeration

Background

Retracing and biomarker characterization of individual circulating tumour cells (CTCs) may potentially contribute to personalized metastatic cancer therapy. This is relevant when a biopsy of the metastasis is complicated or impossible to acquire.

Methods

A novel disc format was used to map and retrace individual CTCs from breast-cancer patients and nucleated cells from healthy blood donors using the CytoTrack platform. For proof of the retracing concept, CTC HER2 characterization by immunofluorescence was tested.

Results

CTCs were detected and enumerated in three of four blood samples from breast-cancer patients and the locations of each individual CTCs were mapped on the discs. Nucleated cells were retraced on seven discs with 96.6%±8.5% recovery on five fields of view on each disc. Shifting of field of view for retracing was measured to 4-29 μm. In a blood sample from a HER2-positive breast-cancer patient, CTC enumeration and mapping was followed by HER2 characterization and retracing to demonstrate downstream immunofluorescence analysis of the CTC.

Conclusion

Mapping and retracing of CTCs enables downstream analysis of individual CTCs for existing and future cancer genotypic and phenotypic biomarkers. Future studies will uncover this potential of the novel retracing technology.

Biomarkers in Breast Cancer: Where Are We and Where Are We Going?

Biomarkers play an important role in the detection and management of patients with breast cancer. Thus, BRCA1/2 mutation testing is used for risk assessment in families with a high prevalence of breast and ovarian cancer. Following a diagnosis of breast cancer, measurement of multi-analyte profiles such as uPA/PAI-1 or Oncotype DX may be used for determining prognosis and identifying lymph node-negative patients who may be spared from having to receive adjuvant chemotherapy. Other -gene tests such as the PAM50 ROR, Breast Cancer Index, and EndoPredict have been reported to predict the development of late recurrences and thus may be of value in selecting patients for extended hormone therapy. Mandatory assays include estrogen receptors for identification of endocrine-sensitive cancers and HER2 in selecting patients for treatment with anti-HER2 therapy (e.g., trastuzumab, lapatinib, pertuzumab, and ado-trastuzumab emtansine). Finally, serum biomarkers such as CA 15-3 or CEA may be used in monitoring therapy in patients with advanced disease receiving systemic therapy. Promising new biomarkers undergoing evaluation include circulating tumor cells and circulating tumor-derived DNA.

Network-based approaches for drug response prediction and targeted therapy development in cancer

Signaling pathways implicated in cancer create a complex network with numerous regulatory loops and redundant pathways. This complexity explains frequent failure of one-drug-one-target paradigm of treatment, resulting in drug resistance in patients. To overcome the robustness of cell signaling network, cancer treatment should be extended to a combination therapy approach. Integrating and analyzing patient high-throughput data together with the information about biological signaling machinery may help deciphering molecular patterns specific to each patient and finding the best combinations of candidates for therapeutic targeting. We review state of the art in the field of targeted cancer medicine from the computational systems biology perspective. We summarize major signaling network resources and describe their characteristics with respect to applicability for drug response prediction and intervention targets suggestion. Thus discuss methods for prediction of drug sensitivity and intervention combinations using signaling networks together with high-throughput data. Gradual integration of these approaches into clinical routine will improve prediction of response to standard treatments and adjustment of intervention schemes.

Utility of creatinine/cystatin C ratio as a predictive marker for adverse effects of chemotherapy in lung cancer: A retrospective study

Objective

To determine whether the creatinine/cystatin C (Cr/CysC) ratio, which is influenced by muscle mass, can be used as a predictive marker of the adverse effects of chemotherapy.

Methods

This single-centre, retrospective, observational study assessed patients with lung cancer. Serum Cr and CysC levels were measured once within 1 month prior the commencement of chemotherapy.

Results

A total of 25 patients with lung cancer were enrolled in the study: 22 received first-line therapy; three received second-line therapy. A significant difference was noted regarding the Cr/CysC ratios between patients with nonsmall-cell lung cancer (NSCLC) and those with small-cell lung cancer (0.78 versus 0.92, respectively). A significant difference was also noted in the Cr/CysC ratios of patients with NSCLC with toxicity grades <3 and ≥3 (0.84 versus 0.70, respectively). Similar findings were observed in patients with NSCLC who received platinum-based combination therapy (toxicity grade < 3, 0.85; toxicity grade ≥3, 0.69).

Conclusion

The Cr/CysC ratio could serve as a useful predictive marker for chemotherapy-related adverse effects in patients with NSCLC.

Validation of new cancer biomarkers: a position statement from the European group on tumor markers

BACKGROUND

Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use.

CONTENT

In this review, we discuss the key steps in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before initiation of the study.

SUMMARY

Application of the methodology outlined above should result in a more efficient and effective approach to the development of cancer biomarkers as well as the reporting of cancer biomarker studies. With rigorous application, all stakeholders, and especially patients, would be expected to benefit.

Immunohistochemistry - microarray analysis of patients with peritoneal metastases of appendiceal or colorectal origin

BACKGROUND

The value of immunohistochemistry (IHC)-microarray analysis of pathological specimens in the management of patients is controversial, although preliminary data suggest potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM) and the feasibility of this technique in this population.

METHODS

We retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular Intelligence(™) testing. IHC, microarray, FISH, and mutational analysis were included and stratified by Peritoneal Carcinomatosis Index (PCI) score, histology, and treatment characteristics. Statistical analysis was performed using non-parametric tests.

RESULTS

Our study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65) years, with 11 (68%) female. The median PCI score of the patients was 17 (IQR 10-25). Hyperthermic intra-peritoneal chemoperfusion was performed in 4 (80%) patients with appendiceal primary tumors and 4 (36%) with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p = 0.06). IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n = 7) patients, which was not associated with previous use of chemotherapy (p > 0.20 for 5-FU/LV, Irinotecan and Oxaliplatin).

CONCLUSION

In a small sample of patients with PM, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.