Oncotarget

Overcoming Aromatase Inhibitor Resistance in Breast Cancer: A New Therapeutic Strategy

Most breast cancers depend on estrogen to grow. This dependence explains why hormone-based treatments, such as aromatase inhibitors, are among the most effective therapies for estrogen receptor–positive breast cancer. Despite their success, these treatments do not work indefinitely for all patients. Over time, many tumors adapt to estrogen deprivation and continue to survive, grow, and spread. This process, known as aromatase inhibitor resistance, represents a major clinical challenge and is often associated with more aggressive disease and poorer outcomes. One reason resistant breast tumors are difficult to treat is that cancer cells adapt their internal signaling systems. Instead of relying on estrogen, they activate alternative growth pathways, including the MAPK and PI3K/AKT pathways. These pathways promote cell survival, movement, and resistance to therapy and are frequently driven by proteins such as KRAS and related G-proteins, which have historically been difficult to target. A recent study published in Oncotarget suggests now that a new class of compounds may offer a way to overcome this resistance. Full blog - https://www.oncotarget.org/2026/01/13/overcoming-aromatase-inhibitor-resistance-in-breast-cancer-a-new-therapeutic-strategy/ Paper DOI - https://doi.org/10.18632/oncotarget.28759 Correspondence to - Nazarius S. Lamango - nazarius.lamango@famu.edu Abstract video - https://www.youtube.com/watch?v=8xQEilloO9Q Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28759 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, PCAIs, ROS, MAPK, PI3K/AKT, LTLT-Ca cells To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh MEDIA@IMPACTJOURNALS.COM

New Hypothesis Links HPV E6 and SARS‑CoV‑2 Spike Proteins to Reduced p53 Activity

BUFFALO, NY – January 13, 2026 – A new #hypothesis article was #published in Oncotarget (Volume 17) on January 3, 2026, titled “Hypothesis: HPV E6 and COVID spike proteins cooperate in targeting tumor suppression by p53.” Written by Wafik S. El-Deiry, Oncotarget Editor-in-Chief, from The Warren Alpert Medical School of Brown University and from Lifespan Health System and Brown University, the paper proposes that two viral proteins, HPV E6 and SARS-CoV-2 spike, could jointly reduce the activity of p53, a protein that helps protect cells from becoming cancerous. HPV is already known to drive several cancers, and the hypothesis suggests that additional pressure on p53 could matter for cancer risk or recurrence in some settings. HPV can promote cancer development in part by using its E6 protein, together with a human partner protein called E6-AP, to drive the downregulation of p53. When p53 is weakened, damaged cells may be more likely to survive and continue growing. The new hypothesis asks whether SARS-CoV-2 viral influence could further reduce p53 function in people already affected by HPV. The article highlights studies suggesting that the SARS-CoV-2 spike protein may suppress p53 activity and discusses observations that have raised questions about cancer outcomes after COVID-19 infection or vaccination in certain contexts. It also notes that a search of the literature did not identify clear evidence of direct molecular cooperation between HPV and COVID-19 in suppressing p53, which underscores the need for further studies. “I listened to an interview (https://www.youtube.com/watch?v=tnVMjp9mCA0&t=2s) of Dr. Patrick Soon-Shiong by Chris Cuomo where I learned about a patient named Jim Johnson with a history of HPV-related head and neck cancer who by 2022 had survived his HPV-related cancer for 7 years and then he took the COVID vaccine.” To investigate the presented hypothesis, Dr. El-Deiry proposes epidemiological studies that analyze cancer incidence and recurrence in HPV-positive groups with prior SARS-CoV-2 infection or COVID mRNA vaccination. It also proposes laboratory studies to assess whether HPV E6 and SARS-CoV-2 spike combined reduce p53 function more than either factor alone. Overall, the hypothesis was formulated to focus attention on an HPV and SARS-CoV-2 shared biological target, p53, and to encourage careful studies that separate coincidence from causation. By outlining specific approaches, it aims to help researchers evaluate whether combined viral pressures on tumor-suppressor pathways could contribute to cancer progression. DOI - https://doi.org/10.18632/oncotarget.28823 Correspondence to - Wafik S. El-Deiry - wafik@brown.edu Abstract video - https://www.youtube.com/watch?v=2GJVmpG4fPk Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28823 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, HPV, COVID, p53, spike To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us on social media: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh MEDIA@IMPACTJOURNALS.COM

Evaluation of Cancer Reports Following COVID-19 Vaccination and Infection

BUFFALO, NY – January 8, 2026 – A new #review was #published in Oncotarget (Volume 17) on January 3, 2026, titled “COVID vaccination and post-infection cancer signals: Evaluating patterns and potential biological mechanisms.” Led by Charlotte Kuperwasser from Tufts University School of Medicine and Oncotarget Editor-in-Chief Wafik S. El-Deiry from The Warren Alpert Medical School of Brown University, the review examines published reports describing cancers that appeared after COVID-19 vaccination or SARS-CoV-2 infection. The authors analyze patterns across case reports, small patient series, and large population studies, and explain why these observations are relevant for cancer research and long-term public health monitoring. Cancer remains a major global health concern, and understanding factors that may influence its behavior is important. The review covers reports published between January 2020 and October 2025 that describe cancer diagnoses, recurrence, or unusually rapid disease progression following vaccination or infection. In total, 69 publications were reviewed. Sixty-six article reports, representing more than 300 patients across multiple countries and cancer types; 2 retrospective investigations; and one longitudinal study spanning the pre-pandemic through post-pandemic periods. The review explores how immune responses triggered by infection or vaccination could, in some individuals, influence existing cancer cells or previously dormant disease. Many article reports involved blood cancers such as lymphomas and leukemias and solid tumors, including breast, lung, pancreatic, brain, and skin cancers. Some cases described rapid disease progression or cancers appearing near vaccine injection sites or nearby lymph nodes. These observations are described as hypothesis-generating rather than evidence of risk. In addition to individual case reports, the review examines findings from large population studies in South Korea, Italy, and the United States military. These studies assessed cancer trends over time in vaccinated populations and reported modest associations for certain cancer types. The authors note that these findings are limited by short follow-up periods and potential reporting and detection biases, emphasizing the need for longer-term data. The authors also discuss possible biological explanations for the reported patterns, including temporary immune changes, inflammation, or altered immune surveillance that could affect tumor behavior in people with undetected or controlled cancer. They place these observations within the broader context of how viral infections can interact with cancer biology. “Establishing causality between SARS-CoV-2 infection, COVID-19 vaccination, and cancer requires a level of evidence far beyond temporal association.” Overall, the review identifies significant gaps in current knowledge about possible associations between COVID-19 vaccination and cancer, including limited long-term cancer surveillance, lack of molecular data, and an incomplete understanding of individual susceptibility. The authors emphasize the need for carefully designed studies that integrate clinical, epidemiologic, and biological evidence. Finally, they conclude that examining these reported patterns is important for advancing cancer research and supporting informed public health discussions. DOI - https://doi.org/10.18632/oncotarget.28824 Correspondence to - Charlotte Kuperwasser - charlotte.kuperwasser@tufts.edu, and Wafik S. El-Deiry - wafik@brown.edu Abstract video - https://www.youtube.com/watch?v=5_-AaojOoR8 To learn more about Oncotarget, please visit https://www.oncotarget.com. MEDIA@IMPACTJOURNALS.COM

Colorectal Cancer Survival Predicted by AI Using Clinical and Molecular Features

BUFFALO, NY - December 17, 2025 – A new #research paper was #published in Oncotarget (Volume 16) on December 15, 2025, titled “Machine learning-based survival prediction in colorectal cancer combining clinical and biological features.” In this study, led by Lucas M. Vieira from the University of Brasília and the University of California San Diego, researchers used machine learning to predict survival in patients with colorectal cancer. They built a model by combining biological markers with clinical data. This approach could help improve prognosis and guide treatment strategies for one of the world’s most common and deadly cancers. The team analyzed data from over 500 patients, using clinical details such as age, chemotherapy status, and cancer stage, along with molecular features like gene expression and microRNAs. Their goal was to improve how clinicians identify high-risk patients and make outcome predictions more precise. Researchers evaluated three different patient data scenarios using different machine learning techniques. The best-performing was an adaptive boosting model, which achieved 89.58% accuracy. This approach showed that integrating clinical and biological data led to significantly better predictions than using either data type alone. Among the biological markers, the gene E2F8 was consistently influential in all patient groups and is known to play a role in tumor growth. Other important markers included WDR77 and hsa-miR-495-3p, which are also associated with cancer development. Key clinical predictors included cancer stage, patient age, lymph node involvement, and whether chemotherapy was administered. “The proposed method combines biological and clinical features to predict patient survival, using as input data from patients from the United States, available in the TCGA database.” Unlike earlier models that relied on either clinical or molecular data alone, this study demonstrates the added value of combining both. Ensemble methods, which merge multiple learning algorithms, provided more stable and consistent results across all patient groups tested. These research findings could lead to new tools that help clinicians better predict how a patient's disease might progress or respond to treatment. The study also highlights the importance of collecting complete clinical information, such as lifestyle factors, which were missing from the dataset but could enhance future predictions. Overall, the study demonstrated how machine learning can support more accurate and personalized survival predictions in colorectal cancer. It also points to potential future research on markers like E2F8, which may be useful for monitoring or targeted therapy. DOI - https://doi.org/10.18632/oncotarget.28783 Correspondence to - Lucas M. Vieira - lvieira@health.ucsd.edu Abstract video - https://www.youtube.com/watch?v=cy7UL5ZUKuI Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28783 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, colorectal cancer, machine learning, feature selection, non-coding RNAs, genes To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us on social media: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh MEDIA@IMPACTJOURNALS.COM

Comprehensive Genomic Profiling in Cancer: Insights from Over 10,000 Tumors

Cancer treatment is moving toward a more precision-based approach, where therapies are guided not just by the tumor’s location but also by its genetic features. Mutations in cancer cells can point to specific drugs that may be more effective for certain patients. However, detecting these mutations often requires broad and detailed analysis. This is where comprehensive genomic profiling becomes especially important. One of the main challenges in cancer care is that many existing genetic tools focus on only a limited number of mutations. As a result, some treatment opportunities may be missed. Certain mutations are also difficult to detect because they occur at low levels or exist in complex forms, such as gene fusions. Without advanced screening methods, these changes may go unnoticed. To address these challenges, researchers from Exact Sciences Corporation conducted a large-scale study using a broad genomic screening approach. The findings were recently published in the journal Oncotarget. Full blog - https://www.oncotarget.org/2025/12/15/comprehensive-genomic-profiling-in-cancer-insights-from-over-10000-tumors/ Paper DOI - https://doi.org/10.18632/oncotarget.28757 Correspondence to - Jean-Paul De La O - jdelao@exactsciences.com Abstract video - https://www.youtube.com/watch?v=awiRhDfiMTE Sign up for free Altmetric alerts about this article - https://oncotarget.altmetric.com/details/email_updates?id=10.18632%2Foncotarget.28757 Subscribe for free publication alerts from Oncotarget - https://www.oncotarget.com/subscribe/ Keywords - cancer, solid tumors, comprehensive genomic profiling, matched therapy, gene fusions, limit of detection To learn more about Oncotarget, please visit https://www.oncotarget.com and connect with us: Facebook - https://www.facebook.com/Oncotarget/ X - https://twitter.com/oncotarget Instagram - https://www.instagram.com/oncotargetjrnl/ YouTube - https://www.youtube.com/@OncotargetJournal LinkedIn - https://www.linkedin.com/company/oncotarget Pinterest - https://www.pinterest.com/oncotarget/ Reddit - https://www.reddit.com/user/Oncotarget/ Spotify - https://open.spotify.com/show/0gRwT6BqYWJzxzmjPJwtVh MEDIA@IMPACTJOURNALS.COM