Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Gallagher, Rosa I.; Wulfkuhle, Julia; Wolf, Denise M.; Brown-Swigart, Lamorna; Yau, Christina; O’Grady, Nicholas; Basu, Amrita; Lu, Ruixiao; Campbell, Michael J.; Magbanua, Mark J.; Coppé, Jean-Philippe; Asare, Smita M.; Sit, Laura; Matthews, Jeffrey B.; Perlmutter, Jane; Hylton, Nola; Liu, Minetta C.; Symmans, W. Fraser; Rugo, Hope S.; Isaacs, Claudine; DeMichele, Angela M.; Yee, Douglas; Pohlmann, Paula R.; Hirst, Gillian L.; Esserman, Laura J.; van ‘t Veer, Laura J.; Petricoin, Emanuel F.

doi:10.1016/j.xcrm.2023.101312

Cited by 3 publications

(1 citation statement)

References 70 publications

(117 reference statements)

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“…This includes multimodal approaches that involve biomarkers beyond ctDNA and imaging features. For example, the I-SPY2 trial is testing whether gene expression- [49] and protein-based [50] tumor biomarkers can improve the prediction of pathCR to guide treatment selection. Wolf and colleagues in I-SPY2 have created alternative breast cancer subtypes by incorporating these molecular biomarkers into the standard breast cancer subtyping and showed improved performance in predicting treatment response [49].…”

Section: Future Directionsmentioning

confidence: 99%

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Magbanua,

Li,

van ’t Veer

2024

Cancers

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Biomarkers for evaluating tumor response to therapy and estimating the risk of disease relapse represent tremendous areas of clinical need. To evaluate treatment efficacy, tumor response is routinely assessed using different imaging modalities like positron emission tomography/computed tomography or magnetic resonance imaging. More recently, the development of circulating tumor DNA detection assays has provided a minimally invasive approach to evaluate tumor response and prognosis through a blood test (liquid biopsy). Integrating imaging- and circulating tumor DNA-based biomarkers may lead to improvements in the prediction of patient outcomes. For this mini-review, we searched the scientific literature to find original articles that combined quantitative imaging and circulating tumor DNA biomarkers to build prediction models. Seven studies reported building prognostic models to predict distant recurrence-free, progression-free, or overall survival. Three discussed building models to predict treatment response using tumor volume, pathologic complete response, or objective response as endpoints. The limited number of articles and the modest cohort sizes reported in these studies attest to the infancy of this field of study. Nonetheless, these studies demonstrate the feasibility of developing multivariable response-predictive and prognostic models using regression and machine learning approaches. Larger studies are warranted to facilitate the building of highly accurate response-predictive and prognostic models that are generalizable to other datasets and clinical settings.

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Section: Future Directionsmentioning

confidence: 99%

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Magbanua,

Li,

van ’t Veer

2024

Cancers

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Harnessing the potential of reverse‐phase protein array technology: Advancing precision oncology strategies

Masuda,

Nakagawa,

Kondo

2024

Cancer Science

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The last few decades have seen remarkable strides in the field of cancer therapy. Precision oncology coupled with comprehensive genomic profiling has become routine clinical practice for solid tumors, the advent of immune checkpoint inhibitors has transformed the landscape of oncology treatment, and the number of cancer drug approvals has continued to increase. Nevertheless, the application of genomics‐driven precision oncology has thus far benefited only 10%–20% of cancer patients, leaving the majority without matched treatment options. This limitation underscores the need to explore alternative avenues with regard to selecting patients for targeted therapies. In contrast with genomics‐based approaches, proteomics‐based strategies offer a more precise understanding of the intricate biological processes driving cancer pathogenesis. This perspective underscores the importance of integrating complementary proteomic analyses into the next phase of precision oncology to establish robust biomarker‐drug associations and surmount challenges related to drug resistance. One promising technology in this regard is the reverse‐phase protein array (RPPA), which excels in quantitatively detecting protein modifications, even with limited amounts of sample. Its cost–effectiveness and rapid turnaround time further bolster its appeal for application in clinical settings. Here, we review the current status of genomics‐driven precision oncology, as well as its limitations, with an emphasis on drug resistance. Subsequently, we explore the application of RPPA technology as a catalyst for advancing precision oncology. Through illustrative examples drawn from clinical trials, we demonstrate its utility for unraveling the molecular mechanisms underlying drug responses and resistance.

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Prokaryotic cell membrane‑based protein technologies (Review)

Suhaib Al Huq,

Raja,

Oviya

2024

World Acad Sci J

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The biological cell membranes play a crucial role in living tissues through a heterogeneity of metabolic processes, such as apoptosis, necrosis, autophagy, cell signalling processes and metabolic disorders. Due to the sensitive nature of cell membranes and proteins, the utilization of specialized instruments for carrying out biological experiments such as extraction, isolation, gene expression and protein expression analyses is required. Currently, there are several instruments available for performing biological experiments. The present study selectively discusses the protein bioanalytical techniques, including electrophoresis techniques, chromatographic techniques, sequencing approaches and computational approaches that have been created as a result of difficulties in researching membrane protein and glycoproteomic techniques. Since these techniques have provided an efficient strategy with which to enrich and characterize membrane and plasma-membrane proteomes, some of the recent advancements are also discussed. In addition, the present study focuses particularly on prokaryotic organisms for a better understanding of cell membrane protein technologies. Hopefully, a summary of these studies will help future researchers to understand the gaps behind the technique and its advances.

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Protein signaling and drug target activation signatures to guide therapy prioritization: Therapeutic resistance and sensitivity in the I-SPY 2 Trial

Cited by 3 publications

References 70 publications

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Integrating Imaging and Circulating Tumor DNA Features for Predicting Patient Outcomes

Harnessing the potential of reverse‐phase protein array technology: Advancing precision oncology strategies

Prokaryotic cell membrane‑based protein technologies (Review)

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