Under the auspices of the College of American Pathologists, the current state of knowledge regarding pathologic prognostic factors (factors linked to outcome) and predictive factors (factors ...predicting response to therapy) in colorectal carcinoma was evaluated. A multidisciplinary group of clinical (including the disciplines of medical oncology, surgical oncology, and radiation oncology), pathologic, and statistical experts in colorectal cancer reviewed all relevant medical literature and stratified the reported prognostic factors into categories that reflected the strength of the published evidence demonstrating their prognostic value. Accordingly, the following categories of prognostic factors were defined. Category I includes factors definitively proven to be of prognostic import based on evidence from multiple statistically robust published trials and generally used in patient management. Category IIA includes factors extensively studied biologically and/or clinically and repeatedly shown to have prognostic value for outcome and/or predictive value for therapy that is of sufficient import to be included in the pathology report but that remains to be validated in statistically robust studies. Category IIB includes factors shown to be promising in multiple studies but lacking sufficient data for inclusion in category I or IIA. Category III includes factors not yet sufficiently studied to determine their prognostic value. Category IV includes factors well studied and shown to have no prognostic significance.
The medical literature was critically reviewed, and the analysis revealed specific points of variability in approach that prevented direct comparisons among published studies and compromised the quality of the collective data. Categories of variability recognized included the following: (1) methods of analysis, (2) interpretation of findings, (3) reporting of data, and (4) statistical evaluation. Additional points of variability within these categories were defined from the collective experience of the group. Reasons for the assignment of an individual prognostic factor to category I, II, III, or IV (categories defined by the level of scientific validation) were outlined with reference to the specific types of variability associated with the supportive data. For each factor and category of variability related to that factor, detailed recommendations for improvement were made. The recommendations were based on the following aims: (1) to increase the uniformity and completeness of pathologic evaluation of tumor specimens, (2) to enhance the quality of the data needed for definitive evaluation of the prognostic value of individual prognostic factors, and (3) ultimately, to improve patient care.
Factors that were determined to merit inclusion in category I were as follows: the local extent of tumor assessed pathologically (the pT category of the TNM staging system of the American Joint Committee on Cancer and the Union Internationale Contre le Cancer AJCC/UICC); regional lymph node metastasis (the pN category of the TNM staging system); blood or lymphatic vessel invasion; residual tumor following surgery with curative intent (the R classification of the AJCC/UICC staging system), especially as it relates to positive surgical margins; and preoperative elevation of carcinoembryonic antigen elevation (a factor established by laboratory medicine methods rather than anatomic pathology). Factors in category IIA included the following: tumor grade, radial margin status (for resection specimens with nonperitonealized surfaces), and residual tumor in the resection specimen following neoadjuvant therapy (the ypTNM category of the TNM staging system of the AJCC/UICC). (ABSTRACT TRUNCATED)
An understanding of tissue data variability in relation to processing techniques during and postsurgery would be desirable when testing surgical specimens for clinical diagnostics, drug development, ...or identification of predictive biomarkers. Specimens of normal and colorectal cancer (CRC) tissues removed during colon and liver resection surgery were obtained at the beginning of surgery and postsurgically, tissue was fixed at 10, 20, and 45 minutes. Specimens were analyzed from 50 patients with primary CRC and 43 with intrahepatic metastasis of CRC using a whole genome gene expression array. Additionally, we focused on the epidermal growth factor receptor pathway and quantified proteins and their phosphorylation status in relation to tissue processing timepoints. Gene and protein expression data obtained from colorectal and liver specimens were influenced by tissue handling during surgery and by postsurgical processing time. To obtain reliable expression data, tissue processing for research and diagnostic purposes needs to be highly standardized.
Molecular tumor markers are often studied in colorectal cancer using immunohistochemistry to determine their prognostic or predictive value. Protein expression is typically assigned a ‘positive' ...score based on a predetermined cutoff. A semiquantitative scoring method that evaluates the percentage of positive tumor cells (0–100%) may provide a better understanding of the prognostic or predictive significance of these markers. The aim of this study was to assess and compare the interobserver agreement of immunohistochemistry scores using a percentage scoring method and three categorical scoring systems. Immunohistochemistry for p53, Bcl-2, vascular endothelial growth factor (VEGF) and apoptotic protease activating factor-1 (APAF-1) was performed on 87 tumor biopsies from patients with rectal carcinoma and scored independently by four pathologists as the percentage of positive tumor cells. Interobserver agreement was assessed by the intraclass correlation coefficient. The intraclass correlation coefficients for p53 and VEGF (>0.6) indicate substantial agreement between observers. The distribution of Bcl-2 and APAF-1 scores in addition to weaker interobserver agreement by percentage scoring suggest that this approach may not be appropriate for these proteins. In conclusion, p53 and VEGF protein expression assessed by immunohistochemistry in colorectal cancer and scored as a percentage of positive tumor cells may be a viable alternative scoring method.
Clinical diagnostic research relies upon the collection of tissue samples, and for those samples to be representative of the in vivo situation. Tissue collection procedures, including post-operative ...ischemia, can impact the molecular profile of the tissue at the genetic and proteomic level. Understanding the influence of factors such as ischemia on tissue samples is imperative in order to develop both markers of tissue quality and ultimately accurate diagnostic tests.
Using NanoPro1000 technology, a rapid and highly sensitive immunoassay platform, the phosphorylation status of clinically relevant cancer-related biomarkers in response to ischemia was quantified in tissue samples from 20 patients with primary colorectal cancer. Tumor tissue and adjacent normal tissue samples were collected and subjected to cold ischemia prior to nanoproteomic analysis of AKT, ERK1/2, MEK1/2, and c-MET. Ischemia-induced relative changes in overall phosphorylation and phosphorylation of individual isoforms were calculated and statistical significance determined. Any differences in baseline levels of phosphorylation between tumor tissue and normal tissue were also analyzed.
Changes in overall phosphorylation of the selected proteins in response to ischemia revealed minor variations in both normal and tumor tissue; however, significant changes were identified in the phosphorylation of individual isoforms. In normal tissue post-operative ischemia, phosphorylation was increased in two AKT isoforms, two ERK1/2 isoforms, and one MEK1/2 isoform and decreased in one MEK1/2 isoform and one c-MET isoform. Following ischemia in tumor tissue, one AKT isoform showed decreased phosphorylation and there was an overall increase in unphosphorylated ERK1/2, whereas an increase in the phosphorylation of two MEK1/2 isoforms was observed. There were no changes in c-MET phosphorylation in tumor tissue.
This study provides insight into the influence of post-operative ischemia on tissue sample biology, which may inform the future development of markers of tissue quality and assist in the development of diagnostic tests.
ObjectiveAccurate estimates of survival guide decision-making for patients and oncologists. Advances in the capacity to measure complex tumour biology and patient factors allow for concurrent ...consideration of clinical, pathological, molecular, and biological markers for prognostication. Clinical prediction tools are a mechanism to combine and personalize these increasingly large amounts of complex information for prognostication.
ApproachWe describe the process of linking routinely collected health data, cancer registry, and pathology report data in two provinces to develop (Ontario, Canada) and validate (Manitoba, Canada) a clinical prediction tool in esophageal cancer. We compared the performance of a base model restricted to patient and disease characteristics available prior to surgical resection (e.g., age, sex, histology, comorbidities), and a more complex model including pathology specimen details (e.g., tumour stage). Cox proportional hazards models were fit to predict death at three years following resection. Internal and external validity was assessed using overall calibration and optimism corrected c-statistics. Equity was assessed through calibration in predefined patient subgroups.
Results2124 patients who underwent surgical resection for esophageal cancer between May 1, 2004 and June 30, 2016 for whom a pathology record was available were included in the study cohort. Median age was 66, with 80% males and 85% adenocarcinomas. Survival data were available until March 31, 2020. The model with pathology data had superior discrimination and calibration (calibration slope of 1.02 and intercept -0.01, and optimism-corrected c-statistic 0.77), compared to the base model (calibration slope of 0.95, intercept 0.02, and c-statistic 0.60). External validation is ongoing.
ConclusionOur study demonstrates that prediction models for cancer prognosis built solely on data from health administrative databases may be unreliable. The addition of high-quality pathology report data from electronic medical records or population-based cancer registries is necessary for accurate estimation. Our work provides a framework for combining administrative and clinical data which could be applied to the development of other clinical prediction models.
To determine whether sentinel lymph node (LN) sampling (SLNS) could reduce the number of nodes required to characterize micrometastatic disease (MMD) in patients with potentially curable colon ...cancer.
Cancer and Leukemia Group B 80001 was a study to determine whether SLNS could identify a subset of LNs that predicted the status of the nodal basin for resectable colon cancer and, therefore, could be extensively evaluated for the presence of micrometastases. Patients enrolled onto this study underwent SLNS after injection of 1% isosulfan blue, and both sentinel nodes (SNs) and non-SNs obtained during primary tumor resection were sectioned at multiple levels and stained using anti-carcinoembryonic antigen and anticytokeratin antibodies.
Using standard histopathology, SNs failed to predict the presence of nodal disease in 13 (54%) of 24 node-positive patients. Immunostains were performed for patients whose LNs were negative by standard histopathology. Depending on the immunohistochemical criteria used to assign LN positivity, SN examination resulted in either an unacceptably high false-positive rate (20%) or a low sensitivity for detection of MMD (40%).
By examining both SNs and non-SNs, this multi-institutional study showed that SNs did not accurately predict the presence of either conventionally defined nodal metastases or MMD. As a result, SLNS is not a useful technique for the study of MMD in patients with colon cancer.
Human biological specimens (biospecimens) are increasingly important for research that aims to advance human health. Yet, despite significant proliferation in specimen-based research and discoveries ...during the past decade, research remains challenged by the inequitable access to high-quality biospecimens that are collected under rigorous ethical standards. This is primarily caused by the complex level of control and ownership exerted by the myriad of stakeholders involved in the biospecimen research process. This article discusses the ethical model of custodianship as a framework for biospecimen-based research to promote fair research access and resolve issues of control and potential conflicts between biobanks, investigators, human research participants (human subjects), and sponsors. Custodianship is the caretaking obligation for biospecimens from initial collection to final dissemination of research findings. It endorses key practices and operating principles for responsible oversight of biospecimens collected for research. Embracing the custodial model would ensure transparency in research, fairness to human research participants, and shared accountability among all stakeholders involved in biospecimen-based research.
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