publication date: Nov. 20, 2020
In vitro fertilization does not increase the risk of ovarian cancer
A new paper published in JNCI: Journal of the National Cancer Institute indicates that receiving assisted reproductive technology does not increase the risk women have for developing ovarian cancer.
Previous research indicated that women who use assisted reproductive technology in order to have a successful pregnancy could potentially be at risk for ovarian cancer and non-malignant borderline ovarian tumors due to excess stimulation of the ovaries.
Since the introduction of assisted reproductive technology—including in vitro fertilization, intracytoplasmic sperm injection, and cryopreservation of embryos—four decades ago, some researchers have raised concerns that such technology might increase the risk of ovarian tumors. Researchers have proposed that this could potentially be due to large increases of sex hormone levels and multiple punctures disrupting ovarian tissue.
Because of the worldwide increase in the use of fertility treatments and the poor prognosis of ovarian cancer, it is important to examine the association between fertility treatments and long-term risk of ovarian tumors.
Several epidemiological studies have investigated the association between such treatments and risk of ovarian tumors, with inconsistent results. In 2013, two meta-analyses were published showing that women who received fertility treatments were more likely to develop ovarian cancer compared with the general population. But it remained unclear if fertility treatments caused women to develop ovarian cancer or if the association could be due to other factors, such as infertility itself.
Researchers here were able to link a database on use of assisted reproductive technology treatment procedures in the Netherlands with national cancer registries to see if an excess risk of ovarian tumors resulted.
This nationwide cohort study included 30,625 women who received ovarian stimulation for ART between 1983 and 2001 and 9,988 infertile women who did not receive such treatment. Incident invasive and borderline ovarian tumors were ascertained through linkage with the Netherlands Cancer Registry and the Dutch Pathology Registry. The researchers investigated risks of ovarian tumors in infertile women who received ovarian stimulation for assisted reproductive technology compared with the risks in the general population and with infertile women who received no such treatment.
After a median follow-up of 24 years, researchers observed 158 invasive cancers and 100 borderline ovarian tumors. No increased risk of ovarian cancer was found in women who received assisted reproductive technology treatment compared with infertile women who did not receive the treatment. Even after more than 20 years the risk of ovarian cancer was not increased. Compared with women in the general Dutch population, women who received assisted reproductive technology did have a higher risk of ovarian cancer, but this appeared to be mainly caused by the higher proportion of women who received assisted reproductive technology who remained childless. Childlessness has been shown to be a strong risk factor for ovarian cancer. Among assisted reproductive technology-treated women in the study, ovarian cancer risk decreased with a larger number of successful for assisted reproductive technology cycles (resulting in childbirth).
Women who received such treatment appear to have an almost two-fold increased risk of borderline ovarian tumors, both when compared with the general population and with infertile women not receiving the treatment. However, risks of borderline ovarian tumors did not increase after more treatment cycles or after longer follow-up. This suggests that the increased risks observed for borderline ovarian tumors might be due to underlying patient characteristics rather than the treatment itself. Borderline tumors are rare in the general population and are generally easy to treat.
“Reassuringly, women who received ovarian stimulation for assisted reproductive technology do not have an increased risk of malignant ovarian cancer, not even in the long run,” lead author Flora E. van Leeuwen said in a statement. “However, it is important to realize that even with the long follow-up in our study, the median age of the women at end of follow-up was only 56 years. As the incidence of ovarian cancer in the population increases at older ages, it is important to follow assisted reproductive technology-treated women even longer.”
UCLA researchers find patients with lung cancer most likely to respond to immunotherapy
Researchers at the UCLA Jonsson Comprehensive Cancer Center found patients with a particular type of human leukocyte antigen (HLA), a protein scaffold involved in presenting pieces of proteins described as peptides to the immune system, were particularly likely to benefit from immunotherapy.
This research explained a surprising finding seen among patients in the clinic.
The data, published in Nature Cancer, focused on a type of HLA called B44, which is present in approximately half of people. In melanoma, patients with HLA-B44 tend to do well with immunotherapy, but in non-small cell lung cancer, the most common type of lung cancer, most people with HLA-B44 did not do as well as people without HLA-B44. In the study, authors figured out that the different responses were driven by the different types of mutations that are common in each of the cancer subtypes.
“Finding out that immunotherapy in HLA-B44 patients performed differently in non-small cell lung cancer than melanoma really set us off on this journey to dive down into how HLA-B44 works,” lead author Amy Cummings, clinical instructor of hematology/oncology at the David Geffen School of Medicine at UCLA and member of the Jonsson Cancer Center, said in a statement. “Usually you would think that for two types of cancers that generally respond well to immunotherapy, there would be similar principles in terms of characteristics of patients who benefit, but that’s not the case in this instance.”
To investigate the role of HLA in immunotherapy response, UCLA researchers performed whole-exome sequencing on melanoma and non-small cell lung cancer tumors and blood samples. Whole-exome sequencing looks at the protein-making genes and the mutations that may be present in the cancer.
Mutations in protein-making genes often lead to a peptide that the immune system can recognize as abnormal, called a neoepitope. The team predicted the neoepitopes generated by patients’ mutations to identify which would most effectively bind to HLA-B44 and be presented to immune cells. With this information, they analyzed treatment outcomes, including survival.
Through these tests, the researchers found that in HLA-B44 non-small cell lung cancer patients, only those who had neoepitopes similar to those commonly found in melanoma had good responses to immunotherapy. More importantly, those responses tended to be durable, meaning non-small cell lung cancer patients with HLA-B44 and melanoma-like neoepitopes had responses to immunotherapy that lasted for years, some longer than five years.
“This certainly has a lot of implications for how we run clinical trials and may be able to help us stratify patients much better in terms of their likelihood of response to immunotherapy,” Cummings said.
“From the time that we discovered the contradictory outcomes in HLA-B44 patients with melanoma and non-small cell lung cancer, we became fascinated by the mechanism that could explain this,” senior author Edward Garon, professor of hematology/oncology and director of the signal transduction and therapeutics program at the Jonsson Cancer Center, said in a statement. “While seeking this explanation, we gained important insight into how the immune system identifies tumors. We hope to eventually harness these findings to design therapies that can further enhance the immune response against tumors in specific patients.”
AI can pick the best candidates for skin cancer treatment
Researchers at NYU Grossman School of Medicine and Perlmutter Cancer Center trained a computer to tell which skin cancer patients may benefit from drugs that keep tumors from shutting down the immune system’s attack on them.
The study showed that an artificial intelligence tool can predict which patients with a specific type of skin cancer would respond well to such immunotherapies in four out of five cases. Specifically, the study examined patients with metastatic melanoma.
While the drug class studied, immune checkpoint inhibitors, has been more effective for many patients than traditional chemotherapies, half of patients do not respond to them. Researchers say the drugs may cause side effects in many of them, and are also expensive.
“Our findings reveal that artificial intelligence is a quick and easy method of predicting how well a melanoma patient will respond to immunotherapy,” first author Paul Johannet, a postdoctoral fellow at NYU Langone Health and its Perlmutter Cancer Center, said in a statement.
The study, published in Clinical Cancer Research, is the first to explore artificial intelligence, or machine learning, to predict a melanoma patient’s response to immune checkpoint inhibitors, the investigators said. The team designed their computer program to learn how to get better at a task but without being told exactly how. Such programs build mathematical models that enable decision-making based on data examples fed into them, with the program getting smarter as the amount of training data grows.
For the investigation, the researchers collected 302 images of tumor tissue samples from 121 men and women treated for metastatic melanoma with immune checkpoint inhibitors at NYU Langone hospitals. Then, they divided these slides into 1.2 million portions of pixels, the small bits of data that make up digital images. These were fed into the computer along with factors such as the severity of the disease, which kind of immunotherapy regimen was used, and whether a patient responded to the treatment.
The study investigators repeated this process with 40 slides from 30 similar patients at Vanderbilt University to determine whether the results held true from a separate hospital system that used different equipment and sampling techniques.
The researchers note that aside from the computer needed to run the program, all of the materials and information used in the Perlmutter technique are already a standard part of cancer management that most, if not all, clinics use.
“A key advantage of our artificial intelligence program over other approaches such as genetic or blood analysis is that it does not require any special equipment,” co-author Aristotelis Tsirigos, director of applied bioinformatics laboratories and clinical informatics at the Molecular Pathology Lab at NYU Langone, said in a statement.
“Even the smallest cancer center could potentially send the data off to a lab with this program for swift analysis,” senior author Iman Osman, Rudolf L. Baer MD Professor of Dermatology at NYU Langone and its Perlmutter Cancer Center, said in a statement.
Osman is also director of the interdisciplinary melanoma program and associate dean for translational research support at NYU Langone.
The algorithm is not yet ready for clinical use until they can boost the accuracy rate from 80% to 90% and test the algorithm at more institutions, Osman said.
The research team next plans to collect more data to better train the computer. Even at its current accuracy, the AI tool can still be used as a screening method to determine which patients across populations would benefit from more in-depth tests before treatment, Osman said.
Phase III trial shows decrease of chemotherapy-induced neutropenia
Phase III trial data shows that a developmental drug, plinabulin, could help keep cancer patients on needed chemotherapy treatments.
Developers at BeyondSpring will now seek FDA approval—citing that the study reached primary endpoints and significant secondary endpoints including decreased rate of grade 4 neutropenia and shorter duration of severe and profound neutropenia.
Plinabulin is sponsored by BeyondSpring.
Plinabulin is a small molecule therapy that is administered through an IV. Data show it significantly decreased incidence of chemotherapy-induced neutropenia when used with standard of care, compared to patients receiving standard of care alone.
CIN is the primary cause of reductions in dose or duration of chemotherapy, which can ultimately lead to less effective cancer treatment. About 86% of oncologists consider CIN a priority among chemotherapy-related treatment decisions because reductions in chemo lead to decreased survival for patients. Plinabulin can potentially be used at any time throughout the chemo cycle.
In addition to seeking FDA approval, BeyondSpring is also expected to seek approval in China in early 2021.
Neratinib in HER2-positive HR-negative early stage breast cancer shows DFS benefit vs. placebo
Nerlynx (neratinib) demonstrates a 5.1% invasive disease-free survival benefit versus placebo in the phase III ExteNET trial evaluating Nerlynx in HER2-positive, hormone receptor-positive early stage breast cancer.
Nerlynx is sponsored by Pierre Fabre. Results from the trial were published in Clinical Breast Cancer.
In the HR+ /< 1 yr patient population, the absolute 5-year invasive disease-free survival benefit versus placebo was 5.1% and absolute 8-year overall survival benefit was 2.1%. The 5-year cumulative incidence of Central Nervous System metastases was 0.7% in the neratinib arm and 2.1% in the placebo arm.
In the HR+/ <1 yr, subgroup of patients who did not achieve pCR upon neo-adjuvant treatment, and hence were at a high risk of disease recurrence, the absolute 5-year iDFS benefit in the neratinib arm versus placebo was 7.4% (HR=0.60; 95% CI 0.33???1.07) and the 8- year overall survival benefit was 9.1% (HR=0.47; 95% CI 0.23- 0.92).
The primary endpoint of the trial was invasive disease-free survival, with overall survival as a key secondary endpoint. Within the European Union, Nerlynx is approved in adult patients with HER2+/HR+ early breast cancer who initiated treatment within one year of completing an adjuvant trastuzumab based regimen.
ExteNET is a multicenter, randomized, double-blind, phase III trial of 2,840 HER2-positive eBC patients who received neratinib after neoadjuvant and/or adjuvant therapy with chemotherapy and trastuzumab.
Patients were stratified by hormone receptor, lymph node status and sequential vs concomitant chemotherapy administration, and randomly assigned to one year of treatment with either oral neratinib 240 mg/day or placebo.