For more than three decades, postoperative chemotherapy-initially fluoropyrimidines and more recently combinations with oxaliplatin-has reduced the risk of tumor recurrence and improved survival for ...patients with resected colon cancer. Although universally recommended for patients with stage III disease, there is no consensus about the survival benefit of postoperative chemotherapy in stage II colon cancer. The most recent adjuvant clinical trials have not shown any value for adding targeted agents, namely bevacizumab and cetuximab, to standard chemotherapies in stage III disease, despite improved outcomes in the metastatic setting. However, biomarker analyses of multiple studies strongly support the feasibility of refining risk stratification in colon cancer by factoring in molecular characteristics with pathologic tumor staging. In stage II disease, for example, microsatellite instability supports observation after surgery. Furthermore, the value of BRAF or KRAS mutations as additional risk factors in stage III disease is greater when microsatellite status and tumor location are taken into account. Validated predictive markers of adjuvant chemotherapy benefit for stage II or III colon cancer are lacking, but intensive research is ongoing. Recent advances in understanding the biologic hallmarks and drivers of early-stage disease as well as the micrometastatic environment are expected to translate into therapeutic strategies tailored to select patients. This review focuses on the pathologic, molecular, and gene expression characterizations of early-stage colon cancer; new insights into prognostication; and emerging predictive biomarkers that could ultimately help define the optimal adjuvant treatments for patients in routine clinical practice.
Critical driver genomic events in colorectal cancer have been shown to affect the response to targeted agents that were initially developed under the 'one gene, one drug' paradigm of precision ...medicine. Our current knowledge of the complexity of the cancer genome, clonal evolution patterns under treatment pressure and pharmacodynamic effects of target inhibition support the transition from a one gene, one drug approach to a 'multi-gene, multi-drug' model when making therapeutic decisions. Better characterization of the transcriptomic subtypes of colorectal cancer, encompassing tumour, stromal and immune components, has revealed convergent pathway dependencies that mandate a 'multi-molecular' perspective for the development of therapies to treat this disease.
Throughout their development, tumors are challenged by the immune system, and they acquire features to evade its surveillance. A systematic view of these traits, which shed light on how tumors ...respond to immunotherapies, is still lacking.
Here, we computed the relative abundance of an array of immune cell populations to measure the immune infiltration pattern of 9,174 tumors of 29 solid cancers. We then clustered tumors with similar infiltration pattern to define immunophenotypes. Finally, we identified genomic and transcriptomic traits associated to these immunophenotypes across cancer types.
In highly cytotoxic immunophenotypes, we found tumors with low clonal heterogeneity enriched for alterations of genes involved in epigenetic regulation, ubiquitin-mediated proteolysis, antigen presentation, and cell-cell communication, which may drive resistance in combination with the ectopic expression of negative immune checkpoints. Tumors with immunophenotypes of intermediate cytotoxicity are characterized by an upregulation of processes involved in neighboring tissue invasion and remodeling that may foster the recruitment of immunosuppressive cells. Tumors with poorly cytotoxic immunophenotype tend to be of more advanced stages and bear a greater burden of copy number alterations and frequent alterations of cell cycle, hedgehog, β-catenin, and TGFβ pathways, which may cause immune depletion.
We provide a comprehensive landscape of the characteristics of solid tumors that may influence (or be influenced by) the characteristics of their immune infiltrate. These results may help interpret the response of solid tumors to immunotherapies and guide the development of novel drug combination strategies.
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The frequent activation of the PI3K/AKT/mTOR pathway in cancer, and its crucial role in cell growth and survival, has made it a much desired target for pharmacologic intervention. Following the ...regulatory approval of the rapamycin analogs everolimus and temsirolimus, recent years have seen an explosion in the number of phosphoinositide 3-kinase (PI3K) pathway inhibitors under clinical investigation. These include: ATP-competitive, dual inhibitors of class I PI3K and mTORC1/2; "pan-PI3K" inhibitors, which inhibit all four isoforms of class I PI3K (α, β, δ, γ); isoform-specific inhibitors of the various PI3K isoforms; allosteric and catalytic inhibitors of AKT; and ATP-competitive inhibitors of mTOR only (and thus mTORC1 and mTORC2). With so many agents in development, clinicians are currently faced with a wide array of clinical trials investigating a multitude of inhibitors with different mechanisms of action, being used both as single agents and in combination with other therapies. Here, we provide a review of the literature, with the aim of differentiating the genomic contexts in which these various types of inhibitors may potentially have superior activity.
The phosphatidylinositol 3-kinase (PI3K) pathway has an important role in cell metabolism, growth, migration, survival and angiogenesis. Drug development aimed at targetable genetic aberrations in ...the PI3K/AKT/mTOR pathway has been fomented by observations that alterations in this pathway induce tumour formation and that inappropriate PI3K signalling is a frequent occurrence in human cancer. Many of the agents developed have been evaluated in early stage clinical trials. This Review focuses on early clinical and translational data related to inhibitors of the PI3K/AKT/mTOR pathway, as these data will likely guide the further clinical development of such agents. We review data from those trials, delineating the safety profile of the agents--whether observed sequelae could be mechanism-based or off-target effects--and drug efficacy. We describe predictive biomarkers explored in clinical trials and preclinical mechanisms of resistance. We also discuss key unresolved translational questions related to the clinical development of inhibitors of the PI3K/AKT/mTOR pathway and propose designs for biomarker-driven trials to address those issues.
It is well established that the PI3K pathway plays a central role in various cellular processes that can contribute to the malignant phenotype. Accordingly, pharmacological inhibition of key nodes in ...this signaling cascade has been a focus in developmental therapeutics. To date, agents targeting upstream receptor tyrosine kinases are best studied and have achieved greatest clinical success. Further downstream, despite efficacy in certain tumor types, the rapalogs have been somewhat disappointing in the clinic. Novel inhibitors of PI3K, Akt, and mTORC1 and 2 are now passing through early phase clinical trials. It is hoped that these agents will circumvent some of the shortcomings of the rapalogs and lead to meaningful benefits for cancer patients.
Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct ...hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the "one test-one drug" paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.
Objective
To identify CT-acquisition parameters accounting for radiomics variability and to develop a post-acquisition CT-image correction method to reduce variability and improve radiomics ...classification in both phantom and clinical applications.
Methods
CT-acquisition protocols were prospectively tested in a phantom. The multi-centric retrospective clinical study included CT scans of patients with colorectal/renal cancer liver metastases. Ninety-three radiomics features of first order and texture were extracted. Intraclass correlation coefficients (ICCs) between CT-acquisition protocols were evaluated to define sources of variability. Voxel size, ComBat, and singular value decomposition (SVD) compensation methods were explored for reducing the radiomics variability. The number of robust features was compared before and after correction using two-proportion
z
test. The radiomics classification accuracy (
K
-means purity) was assessed before and after ComBat- and SVD-based correction.
Results
Fifty-three acquisition protocols in 13 tissue densities were analyzed. Ninety-seven liver metastases from 43 patients with CT from two vendors were included. Pixel size, reconstruction slice spacing, convolution kernel, and acquisition slice thickness are relevant sources of radiomics variability with a percentage of robust features lower than 80%. Resampling to isometric voxels increased the number of robust features when images were acquired with different pixel sizes (
p
< 0.05). SVD-based for thickness correction and ComBat correction for thickness and combined thickness–kernel increased the number of reproducible features (
p
< 0.05). ComBat showed the highest improvement of radiomics-based classification in both the phantom and clinical applications (
K
-means purity 65.98 vs 73.20).
Conclusion
CT-image post-acquisition processing and radiomics normalization by means of batch effect correction allow for standardization of large-scale data analysis and improve the classification accuracy.
Key Points
• The voxel size (accounting for the pixel size and slice spacing), slice thickness, and convolution kernel are relevant sources of CT-radiomics variability.
• Voxel size resampling increased the mean percentage of robust CT-radiomics features from 59.50 to 89.25% when comparing CT scans acquired with different pixel sizes and from 71.62 to 82.58% when the scans were acquired with different slice spacings.
• ComBat batch effect correction reduced the CT-radiomics variability secondary to the slice thickness and convolution kernel, improving the capacity of CT-radiomics to differentiate tissues (in the phantom application) and the primary tumor type from liver metastases (in the clinical application).
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