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Residual Cancer

Residual Cancer: The persistent presence of cancer cells following initial treatment, often posing significant challenges in eradicating the disease.
Effective management of residual cancer requires a deep understanding of the underlying biology and optimization of treatment protocols.
Explore the latest research, pre-prints, and patented approaches using the powerful AI-driven comparisons of PubCompare.ai to uncover the most effective strategies for managing residual cancer and improving patient outcomes.
Start your jouney today to unlock key insights and find the optimal treatments for this persistent condition.

Most cited protocols related to «Residual Cancer»

1
Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer
Cited 66 times
Differentially expressed probe sets in two responder groups: pCR or minimal residual cancer burden (RCB-I) defining excellent response, versus moderate or extensive residual cancer burden (RCB-II/III) defining partial response20 (link) were identified separately in ER+/HER2− and ER−/HER2− training cases using a robust unequal variance t-statistic under a bootstrap scheme. The 209 and 244 probe sets that were significant in at least 30% of the bootstrap replicates in the two cohorts were selected as candidates. Subsequently, a multivariate penalized optimization algorithm, gradient directed regularization, was then used with maximum penalization to select a minimal signature that maximized the area under the ROC curve (AUC) under complete cross-validation.28 The final response predictors used 39 and 55 probe sets for the ER+/HER2− and ER−/HER2− cohorts respectively. Risk scores calculated as the weighted sum of the standardized log2-transformed expression signal of the signature probe sets were dichotomized at zero for both cohorts to predict “responders” (positive scores) or “non-responders” (negative scores).
A similar procedure was followed to develop the predictor for resistance by comparing patients with extensive residual disease (RCB-III) after neoadjuvant chemotherapy treatment versus remaining patients. The final predictor of extensive residual disease used 73 and 54 probe sets for ER+/HER2−and ER−/HER2− subsets respectively (Supplemental Appendix).
Hatzis C., Pusztai L., Valero V., Booser D.J., Esserman L., Lluch A., Vidaurre T., Holmes F., Souchon E., Martin M., Cotrina J., Gomez H., Hubbard R., Chacón J.I., Ferrer-Lozano J., Dyer R., Buxton M., Gong Y., Wu Y., Ibrahim N., Andreopoulou E., Ueno N.T., Hunt K., Yang W., Nazario A., DeMichele A., O’Shaughnessy J., Hortobagyi G.N, & Symmans W.F. (2011). GENOMIC PREDICTOR OF RESPONSE AND SURVIVAL FOLLOWING TAXANE-ANTHRACYCLINE CHEMOTHERAPY FOR INVASIVE BREAST CANCER. JAMA, 305(18), 1873-1881.
Publication 2011
ERBB2 protein, human Neoadjuvant Chemotherapy Patients Residual Cancer Residual Tumor
2
Breast Cancer Gene Expression Profiling
Cited 31 times
Gene-expression data from 230 stage I to III breast cancers, without individual patient identifiers, were provided to the MAQC project by the University of Texas M.D. Anderson Cancer Center (MDACC) Breast Cancer Pharmacogenomic Program. Gene-expression results were generated from fine-needle aspiration specimens of newly diagnosed breast cancers before any therapy. The biopsy specimens were collected sequentially during a prospective pharmacogenomic marker discovery study approved by the institutional review board between 2000 and 2008. These specimens represent 70% to 90% pure neoplastic cells with minimal stromal contamination [12 (link)]. All patients signed informed consent for genomic analysis of their cancers. Patients received 6 months of preoperative (neoadjuvant) chemotherapy including paclitaxel, 5-fluorouracil, cyclophosphamide, and doxorubicin, followed by surgical resection of the cancer. Response to preoperative chemotherapy was categorized as a pathologic complete response (pCR = no residual invasive cancer in the breast or lymph nodes) or residual invasive cancer (RD). The prognostic value of pCR has been discussed extensively in the medical literature [13 (link)]. Genomic analyses of subsets of this sequentially accrued patient population were reported previously [9 (link),14 (link),15 (link)]. For each endpoint, we used the first 130 cases as a training set to develop prediction models, and the next 100 cases were set aside as independent validation set. Table 1 and Additional file 1 show patient and sample characteristics in the two data sets.
Popovici V., Chen W., Gallas B.G., Hatzis C., Shi W., Samuelson F.W., Nikolsky Y., Tsyganova M., Ishkin A., Nikolskaya T., Hess K.R., Valero V., Booser D., Delorenzi M., Hortobagyi G.N., Shi L., Symmans W.F, & Pusztai L. (2010). Effect of training-sample size and classification difficulty on the accuracy of genomic predictors. Breast Cancer Research : BCR, 12(1), R5.
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Publication 2010
Aspiration Biopsy, Fine-Needle Biopsy Breast Carcinoma Cells Cyclophosphamide Doxorubicin Ethics Committees, Research Fluorouracil Gene Expression Genome Malignant Neoplasm of Breast Malignant Neoplasms Neoadjuvant Chemotherapy Neoplasms Nodes, Lymph Operative Surgical Procedures Paclitaxel Patients Pharmacogenomic Analysis Pharmacotherapy Residual Cancer Therapeutics
3
I-SPY 2: Adaptive Breast Cancer Protocol
Cited 15 times
I-SPY 2 is an ongoing, multicenter, open-label, adaptive phase 2 master protocol or ‘platform’ trial with multiple experimental arms that evaluate novel agents combined with standard neoadjuvant therapy in breast cancers at high risk of recurrence.6 (link) Experimental treatments are compared against a common control arm of standard neoadjuvant therapy, with the primary endpoint being pCR, which is defined as no residual cancer in either breast or lymph nodes at time of surgery. Patients who dropout after starting therapy (with or without withdrawal of consent) or fail to have surgery for any reason are counted as non-pCRs.
Biomarker assessments (HER2, HR, MammaPrint) performed at baseline are used to classify patients into 2×2×2 = 8 prospectively defined subtypes for randomization purposes. In addition to standard IHC and FISH assays, the protocol included a microarray-based assay of HER2 expression (TargetPrintTM). This assay has previously shown high concordance with standard IHC and FISH assays of HER28 (link). The adaptive randomization algorithm assigns patients with biomarker subtypes to competing drugs/arms based on current Bayesian probabilities of achieving pCR within that subtype vs control with 20% of patients assigned to control. Adaptive randomization speeds the identification of treatments that perform better within specific patient subtypes and helps avoid exposing patients to therapies that are unlikely to benefit them (Figure 1A).9 ,10 (link)To assess efficacy, ten clinically relevant biomarker ‘signatures’ were defined in the protocol: All; HR+; HR−; HER2+; HER2−; MP Hi-2; HER2+/HR+; HER2+/HR−; HER2−/HR+; HER2−/HR−. Experimental arms are continually evaluated against control for each of these signatures and “graduate” when and if they demonstrate statistical superiority in pCR rate. Statistical analyses are Bayesian.9 ,11 (link) Graduation requires an 85% Bayesian predictive probability of success in a 300-patient equally randomized neoadjuvant phase 3 trial with a traditional statistical design comparing to the same control arm and primary endpoint, pCR, as in I-SPY 2. (see Supplementary Information). Predictive probabilities of success are power calculations for a 300-patient trial averaged with respect to the current probability distributions of pCR rates for the experimental arm and control.9 ,11 (link) The modest size of this hypothetical future trial means that graduation occurs only when there is compelling evidence of an arm’s efficacy. Accrual to a graduating arm halts immediately, but all patients on the arm and its concurrent controls must complete surgery before graduation is announced. An experimental arm is dropped for futility if its predictive probability of success in a phase 3 trial <10% for all ten signatures. The maximum total number of patients assigned to any experimental arm is 120.
Rugo H.S., Olopade O.I., DeMichele A., Yau C., van ‘t Veer L.J., Buxton M.B., Hogarth M., Hylton N.M., Paoloni M., Perlmutter J., Symmans W.F., Yee D., Chien A.J., Wallace A.M., Kaplan H.G., Boughey J.C., Haddad T.C., Albain K.S., Liu M.C., Isaacs C., Khan Q.J., Lang J.E., Viscusi R.K., Pusztai L., Moulder S.L., Chui S.Y., Kemmer K.A., Elias A.D., Edmiston K.K., Euhus D.M., Haley B.B., Nanda R., Northfelt D.W., Tripathy D., Wood W.C., Lyandres J., Davis S.E., Hirst G.L., Sanil A., Berry D.A, & Esserman L.J. (2016). Adaptive Randomization of Veliparib–Carboplatin Treatment in Breast Cancer. The New England journal of medicine, 375(1), 23-34.
Publication 2016
Acclimatization Biological Assay Biological Markers Breast ERBB2 protein, human Fishes Malignant Neoplasm of Breast Microarray Analysis Neoadjuvant Therapy Nodes, Lymph Operative Surgical Procedures Patients Pharmaceutical Preparations Recurrence Residual Cancer Therapies, Investigational
4
Phase 3 Trial of Platinum-Sensitive Recurrent Ovarian Cancer
Cited 11 times

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Publication 2017
Bevacizumab CA-125 Antigen Cancer of the Fallopian Tube Central Nervous System Conferences Dietary Fiber Disease Progression Endometrium Ethics Committees, Research Inpatient Malignant Neoplasms Neoplasm Metastasis Neoplasms Ovary Patients Peritoneum Pharmacotherapy Placebos Platinum Poly(ADP-ribose) Polymerase Inhibitors Residual Cancer Residual Tumor Serum Treatment Protocols X-Rays, Diagnostic
5
I-SPY 2 Adaptive Breast Cancer Trial
Cited 11 times
I-SPY 2 is an ongoing, multicenter, open-label, adaptive phase 2 ‘platform’ trial with multiple experimental arms that evaluate novel agents combined with standard neoadjuvant therapy in breast cancers at high risk of recurrence.11 (link) Experimental treatments are compared against a common control arm, with the primary endpoint being pathologic complete response (pCR), which is defined as no residual cancer in either the breast or lymph nodes at time of surgery.12 (link)Biomarker assessments (HER2, HR, MammaPrint) performed at baseline are used to classify patients into 2×2×2 = 8 prospectively defined subtypes for randomization purposes. HER2 was assessed by standard IHC and FISH assays, and a microarray-based assay of HER2 expression (TargetPrintTM), previously shown to have high concordance with standard IHC and FISH assay.13 (link) The adaptive randomization algorithm assigns patients with biomarker subtypes to competing drugs/arms based on current Bayesian probabilities of achieving pCR within that subtype vs control with 20% of patients assigned to control. Adaptive randomization speeds the identification of treatments that perform better within specific patient subtypes and helps avoid exposing patients to therapies that are unlikely to benefit them (Figure 1A).1 (link),2 (link)To assess efficacy, ten clinically relevant biomarker ‘signatures’ were defined in the protocol: All; HR+; HR−; HER2+; HER2−; MP Hi-2; HER2+/HR+; HER2+/HR−; HER2−/HR+; HER2−/HR−. Experimental arms are continually evaluated against control for each of these signatures and “graduate” when and if they demonstrate statistical superiority in pCR rate. Statistical analyses are Bayesian.14 (link)Graduation requires an 85% Bayesian predictive probability of success in a 300-patient equally randomized neoadjuvant phase 3 trial with a traditional statistical design comparing to the same control arm as in I-SPY 2 and primary endpoint pCR (see Supplement).14 (link),1 (link) Predictive probabilities of success are power calculations for a 300-patient trial averaged with respect to the current probability distributions of pCR rates for the experimental arm and control.1 (link),14 (link) The modest proposed size means that graduation occurs only when there is compelling evidence of an arm’s efficacy. Accrual to a graduating arm halts immediately, but all patients on the arm and its concurrent controls must complete surgery before graduation is announced. An experimental arm is dropped for futility if its predictive probability of success in a phase 3 trial <10% for all ten signatures. The maximum total number of patients assigned to any experimental arm is 120.
All participating sites received institutional review board approval. A data safety monitoring board meets monthly.
Park J.W., Liu M.C., Yee D., Yau C., van 't Veer L.J., Symmans W.F., Paoloni M., Perlmutter J., Hylton N.M., Hogarth M., DeMichele A., Buxton M.B., Chien A.J., Wallace A.M., Boughey J.C., Haddad T.C., Chui S.Y., Kemmer K.A., Kaplan H.G., Liu M.C., Isaacs C., Nanda R., Tripathy D., Albain K.S., Edmiston K.K., Elias A.D., Northfelt D.W., Pusztai L., Moulder S.L., Lang J.E., Viscusi R.K., Euhus D.M., Haley B.B., Khan Q.J., Wood W.C., Melisko M., Schwab R., Lyandres J., Davis S.E., Hirst G.L., Sanil A., Esserman L.J, & Berry D.A. (2016). Adaptive Randomization of Neratinib in Early Breast Cancer. The New England journal of medicine, 375(1), 11-22.
Publication 2016
Acclimatization Biological Assay Biological Markers Breast Clinical Trials Data Monitoring Committees Dietary Supplements ERBB2 protein, human Ethics Committees, Research Fishes Malignant Neoplasm of Breast Microarray Analysis Neoadjuvant Therapy Nodes, Lymph Operative Surgical Procedures Patients Pharmaceutical Preparations Recurrence Residual Cancer Therapies, Investigational

Most recents protocols related to «Residual Cancer»

1
Gastric Adenocarcinoma Biomarker Expression
We performed this single-center, prospective pilot study at the University of Alberta in Edmonton, Alberta, Canada from January 2018 to January 2022. All human clinical participants consented according to the approved ethics protocol granted by the Health Research Ethics Board of Alberta (Study ID: HREBA.CC-17-0228_REN5). Treatment naïve Stage I-IV sporadic gastric adenocarcinoma patients aged greater than 18 years were included. A subset of patients enrolled was allocated to a second cohort on the basis of receiving curative intent neoadjuvant FLOT chemotherapy (Figure 1). Patients with a known inherited oncogenic germline mutation or hereditary syndrome (i.e., Familial Adenomatous Polyposis) were excluded.
Specimens were retrieved via endoscopic biopsy at the time of diagnosis, screening laparoscopy or at the time of surgical resection at the Walter C Mackenzie Health Sciences Centre or Royal Alexandra Hospital. Normal biopsies were obtained from gastric mucosa greater than 5 cm away from the cancerous lesion or associated gastritis. The initial study protocol retrieved two tissue biopsies for permanent pathology, however, following interim review four biopsies were retrieved thereafter. The presence of cancer in specimens was confirmed by a gastrointestinal pathologist. In the absence of cancer, clinical formalin-fixed paraffin-embedded pathology blocks were retrieved when available. In clinical samples with treatment effect, residual cancer cells were detected using anti-pan cytokeratin (Abcam, clone C-11, ab7753) IHC staining followed by the manual assembly of tissue microarray (TMA) blocks with 4mm cores of regions containing residual tumour.
Our primary outcome for all patients was the difference in expression of selected biomarkers between normal and cancer tissue. In the subgroup of patients receiving neoadjuvant chemotherapy, our primary outcome was the difference in expression between tumour treatment response and incomplete treatment response. We also evaluated the difference in expression of biomarkers in paired samples before and after chemotherapy treatment.
Treatment response was retrieved from clinical pathology reports. The Tumour Regression Score was graded according to the College of American Pathologists and National Comprehensive Cancer Network protocol on a 4-point scale (0 = Complete response, 1 = near complete response, 2 = partial response, 3 = poor or no response)[40 (link)]. In accordance with prior studies, treatment response was expressed as a binary variable consisting of response and incomplete response categories[12 (link)]. Responsive tumours included complete and near-complete responses, whereas incomplete responses included partial, and poor no response. Patients who progressed to metastasis while receiving neoadjuvant treatment were classified as an incomplete response.
Skubleny D., Lin A., Garg S., McLean R., McCall M., Ghosh S., Spratlin J.L., Schiller D, & Rayat G. (2023). Increased CD4/CD8 Lymphocyte ratio predicts favourable neoadjuvant treatment response in gastric cancer: A prospective pilot study. World Journal of Gastrointestinal Oncology, 15(2), 303-317.
Publication 2023
Adenocarcinoma Adenomatous Polyposis Coli Anesthesia, Conduction Biological Markers Biopsy Cells Clone Cells Cytokeratin Diagnosis Endoscopy Formalin Gastritis Germ-Line Mutation Germ Line Homo sapiens Laparoscopy Malignant Neoplasms Microarray Analysis Mucosa, Gastric Neoadjuvant Chemotherapy Neoadjuvant Therapy Neoplasm Metastasis Neoplasms Neoplastic Cell Transformation Paraffin Pathologists Patients Pharmacotherapy Residual Cancer Residual Tumor Specimen Handling Stomach Syndrome Tissues
2
Immunohistochemical Analysis of Colorectal Cancer
The IHC study included patients with colorectal adenocarcinoma with morphologically verified diagnosis, treated in the Department of abdominal oncology, Cancer Research Institute of Tomsk National Research Medical Center (Tomsk, Russia). The study was carried out according to Declaration of Helsinki (from 1964, revised in 1975 and 1983) and was approved by the local committee of Medical Ethics of Tomsk Cancer Research Institute; all patients signed informed consent for the study. Patients were divided as we did for TCGA cohort with the exception that the number of patients in SPARC/SPP1 group differed from S100A4 group: a) with colorectal cancer (common group for SPARC/SPP1) (N=118), b) with colon cancer (N=54), c) with rectal cancer (N=64) (Supplementary Table S2). For S100A4 group: a) with colorectal cancer (common group) (N=197), b) with colon cancer (N=89), c) with rectal cancer (N=107) (Supplementary Table S3). Patients with rectal cancer and cancer of the rectosigmoid junction received neoadjuvant chemotherapy (NAC) or chemoradiotherapy (NCRT). Five-grade Mandard Tumor Regression Grading (TRG) system was used for assessment of response in patients, where TRG1 – no residual cancer, TRG2 – residual isolated cancer cells, TRG3 – fibrosis outgrowing residual cancer, TRG4 – residual cancer outgrowing fibrosis, TRG5 – absence of regressive changes (14 (link)). All patients underwent surgical treatment. In adjuvant regime, according to indications, patients received chemotherapy under the same schemes for up to 6 months. Cases of stage IV disease were excluded.
Kazakova E., Rakina M., Sudarskikh T., Iamshchikov P., Tarasova A., Tashireva L., Afanasiev S., Dobrodeev A., Zhuikova L., Cherdyntseva N., Kzhyshkowska J, & Larionova I. (2023). Angiogenesis regulators S100A4, SPARC and SPP1 correlate with macrophage infiltration and are prognostic biomarkers in colon and rectal cancers. Frontiers in Oncology, 13, 1058337.
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Publication 2023
Abdomen Adenocarcinoma Cancer of Colon Cells Chemoradiotherapy Colorectal Carcinoma Diagnosis Fibrosis Malignant Neoplasms Neoadjuvant Chemotherapy Neoplasms Operative Surgical Procedures Patients Pharmaceutical Adjuvants Pharmacotherapy Rectal Cancer Regional Ethics Committees Residual Cancer SPARC protein, human SPP1 protein, human
3
Neoadjuvant PD1 Blockade with or without CapOx for Rectal Cancer
All patients were discussed in a multidisciplinary team conference. All patients received PD1 blockade (PD1 blockade 200 mg intravenously over 30 min on day 1 of each 21-d cycle) preoperative immunotherapy with or without CapOx chemotherapy (oxaliplatin 130 mg/m2 on day 1 and capecitabine 1000 mg/m2 twice daily on d 1–14, repeated every 3 wk).
The primary tumor response was assessed according to the iRECIST criteria[19 (link)]. Acute toxicity was graded according to the NCI Common Terminology Criteria for Adverse Events 4.0[20 (link)]. After every one or two cycles of neoadjuvant immunotherapy, all patients had complete assessment including computed tomography (CT), magnetic resonance imaging, PET-CT, blood counts, renal biochemistry, hepatobiliary function, thyroid function, cardiac function, and tumor markers (carcinoembryonic antigen and carbohydrate antigen 19-9) to evaluate the general condition and treatment response. The determination of clinical complete response (cCR) was based on Memorial Sloan Kettering Cancer Center standard[21 (link)] and International Watch & Wait Database[22 (link)]. The cCR was defined as no evidence of residual tumor determined by rectum MRI, abdomen/pelvis CT and chest CT, endoscopic physical examination, nomarl CEA and/or digital rectal exam. Pathological staging was based on the 8th edition of the American Joint Committee on Cancer TNM staging system[23 (link)]. Post-treatment response was assessed by NCCN grading: 0 = complete response (ypCR) with no detectable cancer cells; 1 = major response with few residual cancer cells; 2 = partial response; 3 = no or very little response[24 (link)].
Postoperative complications were classified according to the Clavien–Dindo classification[24 (link)].
Li Y.J., Liu X.Z., Yao Y.F., Chen N., Li Z.W., Zhang X.Y., Lin X.F, & Wu A.W. (2023). Efficacy and safety of preoperative immunotherapy in patients with mismatch repair-deficient or microsatellite instability-high gastrointestinal malignancies. World Journal of Gastrointestinal Surgery, 15(2), 222-233.
Publication 2023
Abdominal Cavity BLOOD CA-19-9 Antigen Capecitabine Cells Chest Conferences Endoscopy Fingers Heart Immunotherapy Joints Kidney Malignant Neoplasms Neoadjuvant Therapy Neoplasms Oxaliplatin Patients Pelvis Pharmacotherapy Physical Examination Postoperative Complications Rectum Residual Cancer Residual Tumor Thyroid Gland Tumor Markers X-Ray Computed Tomography
4
Identifying Lung Cancer Recurrence Algorithm
The algorithm was constructed similarly to the previously developed algorithms to identify cancer recurrence from malignant melanoma, bladder, breast, and endometrial cancer by Rasmussen et al13–16 (link) (Figure 1). The end date of primary lung cancer treatment was defined as the date of lung cancer surgery or the date of the last chemotherapy procedure code in case of adjuvant chemotherapy. A subsequent period with no register-based evidence of ongoing malignant disease was required to prevent inclusion of patients with residual disease after completed lung cancer treatment. The final day of this period was 90 days after surgery or 30 days after ended adjuvant chemotherapy treatment, whichever came last. Indicators of ongoing disease was 1) malignant morphology (SNOMED codes M8* and M9*), 2) new diagnosis codes indicating malignant disease (ICD-10: C00*- C96* and D37*-D48*excluding C44* (non-melanoma skin cancer) and C34* (lung cancer)), 3) procedure codes for radiotherapy (BWGC*) or chemotherapy (BWHA*) combined with a malignant diagnosis code (ICD-10: C00*-C96* and D37*-D48*), and 4) UICC stage IV.

Schematic overview of the algorithm.

After the period with no register-based evidence of ongoing malignant disease, the algorithm searched for indicators of cancer recurrence (Figure 1). A patient was defined as being diagnosed with lung cancer recurrence if one of the following six indicators was present:

ICD-10: C349X (lung cancer recurrence diagnosis);

ICD-10: C76*-C79* or C34xM (metastasis diagnosis) and no new primary cancer registered after the conclusion of primary lung cancer treatment;

SNOMED morphology codes M8*-M9* and 7 (malignant recurrence) in the fifth digit;

SNOMED morphology codes M8*-M9* and 4 (direct spread to surrounding tissue) or 6 (malignant metastasis) in the fifth digit and a morphology similar to a morphology code registered within 90 days of the primary lung cancer diagnosis date or date of lung cancer surgery;

Radiotherapy or chemotherapy procedure codes combined with a diagnosis code indicating lung cancer (ICD-10: C34*);

Radiotherapy or chemotherapy procedure codes combined with a diagnosis code indicating metastases (ICD-10: C76*-C79* or C34xM) and no new primary cancer registered after the conclusion of primary lung cancer treatment.

Indicators of recurrence were disregarded if they appeared after ended follow-up in the gold standard. The recurrence date estimated by the algorithm was defined as the first date with a registration of an indicator of recurrence.
Rasmussen L.A., Christensen N.L., Winther-Larsen A., Dalton S.O., Virgilsen L.F., Jensen H, & Vedsted P. (2023). A Validated Register-Based Algorithm to Identify Patients Diagnosed with Recurrence of Surgically Treated Stage I Lung Cancer in Denmark. Clinical Epidemiology, 15, 251-261.
Publication 2023
Breast Chemotherapy, Adjuvant Diagnosis Endometrial Carcinoma Familial Atypical Mole-Malignant Melanoma Syndrome Gold Lung Cancer Lung Diseases Malignant Neoplasms Melanoma Menstruation Disturbances Neoplasm Metastasis Operative Surgical Procedures Patients Pharmaceutical Adjuvants Pharmacotherapy Radiotherapy Recurrence Residual Cancer Residual Tumor Tissues Urinary Bladder
5
Evaluating Tumor-Infiltrating Lymphocytes and Residual Cancer Burden
All specimens were pathologically reviewed. Evaluation of the core-needle
biopsy samples included assessments of stromal TILs and the nuclear and
histologic grades of each breast carcinoma sample. The levels of TILs are
expressed as percentages, as described by the International TIL Working
Group.17 (link) The residual cancer burden (RCB) score,
Miller-Payne grade, residual tumor size, and TILs of the surgical specimens
were determined.18 (link),19 (link) The tumor bed area in samples of patients who
achieved pCR group was marked and collected for high-throughput NGS.
Shin J., Ham B., Seo J.H., Lee S.B., Park I.A., Gong G., Kim S.B, & Lee H.J. (2023). Immune repertoire and responses to neoadjuvant TCHP therapy in HER2-positive breast cancer. Therapeutic Advances in Medical Oncology, 15, 17588359231157654.
Publication 2023
Breast Carcinoma Lymphocytes, Tumor-Infiltrating Neoplasms Operative Surgical Procedures Patients Residual Cancer Residual Tumor

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More about "Residual Cancer"

Residual cancer, the persistent presence of cancer cells following initial treatment, poses significant challenges in eradicating the disease.
Effective management of this condition requires a deep understanding of the underlying biology and optimization of treatment protocols.
Explore the latest research, pre-prints, and patented approaches using the powerful AI-driven comparisons of PubCompare.ai to uncover the most effective strategies for managing residual cancer and improving patient outcomes.
Discover how PubCompare.ai's AI-driven protocol optimization unlocks insights into residual cancer research.
Locate the best protocols from literature, pre-prints, and patents using our powerful AI comparisons.
Optimize your research and find the most effecitve treatments for this persistent condition.
Start your journey today with PubCompare.ai.
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