Management and Clinico-Pathologic Aspects of Non-Melanoma Skin Cancer of the Head and Neck: A Retrospective Institutional Based Study at the Egyptian National Cancer Institute

Background: Reviewing and analyzing the Clinico-pathologic aspects of non-melanoma skin cancer of the head and neck (NMSCHN), type of management, prognostic factors, and disease-free survival (DFS) in a period of 5 years at the National Cancer Institute—Cairo University—Egypt. Materials and Methods: A retrospective study of two hundred patients with NMSCHN was treated at the National Cancer Institute—Cairo University—Egypt from January 2008 to December 2012. The mean follow-up was 6 months (1 - 84 months). Results: 117 males and 83 females with 90% ≥ 50 years old. The scalp (27.5%), the periorbital region (13%), the cheek (12.5%) and the nose (12.5%) are the main anatomical sites affected. BCC represented 71.5% with nodular type (79%) predominance;SCC represented 21% with GII (61.1%) the commonest grade. Surgery was the main modality of treatment (93%) with local flaps only (63.9%) and primary closure (14.7%) were the main surgical options following wide local excision. Positive and close margins were detected in 23.5% of excised specimens. No significant association was found between disease-free survival (DFS) and pathology, treatment modality, the occurrence of complications or safety margin status. Conclusion: NMSCHN lesions should be surgically excised in specialized high volume centers with readily available peripheral margin control and should be operated by senior experienced surgeons.

Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

The Value of Excipients and the Required Understanding of the Biological System in Product Development: An Impactful Example of Curaderm, a Topical Skin Cancer Treatment

The incidences of nonmelanoma skin cancer are increasing worldwide, and the ongoing war on its treatment necessitates the development of effective and non-invasive methods. Through basic and clinical research, non-invasive treatments like Curaderm have been developed, leading to improved quality of life for patients. Excipients, previously considered inactive ingredients, play a crucial role in enhancing the performance of topical formulations. The development of Curaderm emphasizes the importance of understanding the interactions between active ingredients, excipients, and the biological system to create effective and affordable pharmaceutical formulations. The systematic approach taken in the development of Curaderm, starting from the observation of the anticancer activity of natural solasodine glycosides and progressing through toxicological and efficacy studies in cell culture, animals, and humans, has provided insights into the pharmacokinetics and pharmacodynamics of solasodine glycosides. It is crucial to determine these pharmacological parameters within the skin’s biological system for maximal effectiveness and cost-effectiveness of a skin cancer treatment. Curaderm, as a topical treatment for nonmelanoma skin cancer, offers benefits beyond those obtained from other topical treatments, providing hope for improved quality of life for patients.

Unique Clinical Features of Curaderm when Treating Skin Cancers

Basal cell carcinoma is the most common form of skin cancer and the most frequently occurring form of all cancers. Conventional treatments to remove or destroy basal cell carcinoma are indiscriminate and also remove or destroy normal skin cells resulting in compromised cosmetic outcomes. Consequences of these treatments include body-image issues, anxiety, post-traumatic stress disorder, depression, and poorer quality of social and family life. A progressive topical cream formulation, Curaderm, containing the natural BEC glycoalkaloids, have shown to have advantages over conventional treatments. However, comprehensive clinical features of the skin cancer lesions during treatment with Curaderm have to date not been reported. This report shows that using unpublished data from a large number of patients with varying sizes, types and locations of basal cell carcinomas when treated with Curaderm in a phase 3 trial, an initial increase in size of the lesions occur, followed by a reverse course, leading to complete removal of the skin cancer. The specificity and mode of action of Curaderm explains the superior cosmetic outcomes when compared with conventional therapies.

Gold Standard for Skin Cancer Treatment: Surgery (Mohs) or Microscopic Molecular-Cellular Therapy (Curaderm)?

Non-melanoma skin cancers or keratinocyte cancers such as basal cell carcinoma and squamous cell carcinoma make up approximately 80% and 20% respectively, of skin cancers with the 6 million people that are treated annually in the United States. 1 in 5 Americans and 2 in 3 Australians develop skin cancer by the age of 70 years and in Australia it is the most expensive, amassing $1.5 billion, to treat cancers. Non-melanoma skin cancers are often self-detected and are usually removed by various means in doctors’ surgeries. Mohs micrographic surgery is acclaimed to be the gold standard for the treatment of skin cancer. However, a novel microscopic molecular-cellular non-invasive topical therapy described in this article, challenges the status of Mohs procedure for being the acclaimed gold standard.

Chicken skin mucosa surrounding small colorectal cancer could be an endoscopic predictive marker of submucosal invasion

BACKGROUND Chicken skin mucosa(CSM)surrounding colon polyps is a common endoscopic finding with pale yellow-speckled mucosa during a colonoscopy screening.Although reports about CSM surrounding small colorectal cancer are scarce,and its clinical significance in intramucosal and submucosal cancers is unclear,previous studies have suggested it could be an endoscopic predictive marker for colonic neoplastic and advanced polyps.Currently,because of the inaccurate preoperative evaluation by endoscopists,many small colorectal cancers,particularly lesions with a diameter<2 cm,are improperly treated.Therefore,more effective methods are required to better assess the depth of the lesion before treatment.AIM To explore potential markers of small colorectal cancer early invasion under white light endoscopy,providing patients with better treatment alternatives.METHODS This retrospective cross-sectional study included 198 consecutive patients[233 early colorectal cancers(ECCs)]who underwent endoscopy or surgical procedures at the Digestive Endoscopy Center of Chengdu Second People’s Hospital between January 2021 and August 2022.The participants had pathologically confirmed colorectal cancer with a lesion diameter<2 cm and received endoscopic or surgical treatment,including endoscopic mucosal resection and submucosal dissection.Clinical pathology and endoscopy parameters,including tumor size,invasion depth,anatomical position,and morphology,were reviewed.Fisher’s exact test,theχ2 test,and Student’s t-test were used to analyze the patient’s basic characteristics.Logistic regression analysis was used to examine the relationship between morphological characteristics,size,CSM prevalence,and ECC invasion depth under white light endoscopy.Statistical significance was set at P<0.05.RESULTS The submucosal carcinoma(SM stage)was larger than the mucosal carcinoma(M stage)with a significant difference(17.2±4.1 vs 13.4±4.6 mm,P<0.01).M-and SM-stage cancers were common in the left colon;however,no significant differences were found between them(151/196,77%and 32/37,86.5%,respectively,P=0.199).The endoscopic features of colorectal cancer revealed that CSM,depressed areas with clear boundaries,and erosion or ulcer bleeding were more common in the SM-stage cancer group than in the M-stage cancer group(59.5%vs 26.2%,46%vs 8.7%,and 27.3%vs 4.1%,respectively,P<0.05).CSM prevalence in this study was 31.3%(73/233).The positive rates of CSM in flat,protruded,and sessile lesions were 18%(11/61),30.6%(30/98),and 43.2%(32/74),respectively,with significant differences(P=0.007).CONCLUSION CSM-related small colorectal cancer was primarily located in the left colon and could be a predictive marker of submucosal invasion in the left colon.

Ultraviolet radiation-induced non-melanoma skin cancer:Regulation of DNA damage repair and inflammation

Exposure to ultraviolet(UV)radiation is associated with approximately 65%of melanoma cases,and 90%of non-melanoma skin cancers(NMSC),including basal cell carcinoma(BCC)and squamous cell carcinoma(SCC).While the incidence of most other malignancies has either stabilized or declined,that of NMSC has increased and is developing even in younger age groups.NMSCs account for nearly 15,000 deaths,3.5 million new cases,and more than 3 billion dollars a year in medical costs in the United States alone,representing a major public health concern.As sun protection efforts have not been proven effective,targeted chemoprevention strategies are much needed.Skin carcinogenesis by DNA damage is considered a predominant paradigm for UV toxicity.Exposure to UV radiation can activate various oncogenes while inactivating tumor suppressor genes,resulting in inappropriate survival and proliferation of keratinocytes that harbor these damages.Moreover,increasing evidence demonstrate that inflammatory responses by the immune cells within the tumor microenvironment also contribute significantly to skin tumorigenesis.Initiation and progression of skin carcinogenesis mediated by UV radiation involve complex pathways,including those of apoptosis,proliferation,autophagy,DNA repair,checkpoint signaling,metabolism,and inflammation.In this review,we highlight the recent advances in two of these key molecular processes that result in UV-mediated skin carcinogenesis.In particular,we discuss 1)pathways that regulate DNA damage repair and 2)the regulation of the inflammatory process its crosstalk with DNA repair potentially leading to non-melanoma skin carcinogenesis.

Smart MobiNet:A Deep Learning Approach for Accurate Skin Cancer Diagnosis

The early detection of skin cancer,particularly melanoma,presents a substantial risk to human health.This study aims to examine the necessity of implementing efficient early detection systems through the utilization of deep learning techniques.Nevertheless,the existing methods exhibit certain constraints in terms of accessibility,diagnostic precision,data availability,and scalability.To address these obstacles,we put out a lightweight model known as Smart MobiNet,which is derived from MobileNet and incorporates additional distinctive attributes.The model utilizes a multi-scale feature extraction methodology by using various convolutional layers.The ISIC 2019 dataset,sourced from the International Skin Imaging Collaboration,is employed in this study.Traditional data augmentation approaches are implemented to address the issue of model overfitting.In this study,we conduct experiments to evaluate and compare the performance of three different models,namely CNN,MobileNet,and Smart MobiNet,in the task of skin cancer detection.The findings of our study indicate that the proposed model outperforms other architectures,achieving an accuracy of 0.89.Furthermore,the model exhibits balanced precision,sensitivity,and F1 scores,all measuring at 0.90.This model serves as a vital instrument that assists clinicians efficiently and precisely detecting skin cancer.

Application of negative pressure wound therapy after skin grafting in the treatment of skin cancer:A case report

BACKGROUND Skin cancer is a common malignant tumor in dermatology.A large area must be excised to ensure a negative incisal margin on huge frontotemporal skin cancer,and it is difficult to treat the wound.In the past,treatment with skin grafting and pressure dressing was easy to cause complications such as wound infections,subcutaneous effusion,skin necrosis,and contracture.Negative pressure wound therapy(NPWT)has been applied to treat huge frontotemporal skin cancer.CASE SUMMARY Herein,we report the case of a 92-year-old woman with huge frontotemporal skin cancer.The patient presented to the surgery department complaining of ruptured bleeding and pain in a right frontal mass.The tumor was pathologically diagnosed as highly differentiated squamous cell carcinoma.The patient underwent skin cancer surgery and skin grafting,after which NPWT was used.She did not experience a relapse during the three-year follow-up period.CONCLUSION NPWT is of great clinical value in the postoperative treatment of skin cancer.It is not only inexpensive but also can effectively reduce the risk of surgical effusion,infection,and flap necrosis.

Sand Cat Swarm Optimization with Deep Transfer Learning for Skin Cancer Classification

Skin cancer is one of the most dangerous cancer.Because of the high melanoma death rate,skin cancer is divided into non-melanoma and melanoma.The dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin lesions.Sometimes,pathology and biopsy examinations are required for cancer diagnosis.Earlier studies have formulated computer-based systems for detecting skin cancer from skin lesion images.With recent advancements in hardware and software technologies,deep learning(DL)has developed as a potential technique for feature learning.Therefore,this study develops a new sand cat swarm optimization with a deep transfer learning method for skin cancer detection and classification(SCSODTL-SCC)technique.The major intention of the SCSODTL-SCC model lies in the recognition and classification of different types of skin cancer on dermoscopic images.Primarily,Dull razor approach-related hair removal and median filtering-based noise elimination are performed.Moreover,the U2Net segmentation approach is employed for detecting infected lesion regions in dermoscopic images.Furthermore,the NASNetLarge-based feature extractor with a hybrid deep belief network(DBN)model is used for classification.Finally,the classification performance can be improved by the SCSO algorithm for the hyperparameter tuning process,showing the novelty of the work.The simulation values of the SCSODTL-SCC model are scrutinized on the benchmark skin lesion dataset.The comparative results assured that the SCSODTL-SCC model had shown maximum skin cancer classification performance in different measures.

Skin Cancer Classification Using Transfer Learning by VGG16 Architecture (Case Study on Kaggle Dataset)

Skin cancer is a serious and potentially life-threatening disease that affects millions of people worldwide. Early detection and accurate diagnosis are critical for successful treatment and improved patient outcomes. In recent years, deep learning has emerged as a powerful tool for medical image analysis, including the diagnosis of skin cancer. The importance of using deep learning in diagnosing skin cancer lies in its ability to analyze large amounts of data quickly and accurately. This can help doctors make more informed decisions about patient care and improve overall outcomes. Additionally, deep learning models can be trained to recognize subtle patterns and features that may not be visible to the human eye, leading to earlier detection and more effective treatment. The pre-trained Visual Geometry Group 16 (VGG16) architecture has been used in this study to classification of skin cancer images, and the images have been converted into other color scales, there are named: 1) Hue Saturation Value (HSV), 2) YCbCr, 3) Grayscale for evaluation. Results show that the dataset created with RGB and YCbCr images in field condition was promising with a classification accuracy of 84.242%. The dataset has also been evaluated with other popular architectures and compared. The performance of VGG16 with images of each color scale is analyzed. In addition, feature parameters have been extracted from the different layers. The extracted layers were felt with the VGG16 to evaluate the ability of the feature parameters in classifying the disease.

Mucosa color and size may indicate malignant transformation of chicken skin mucosa-positive colorectal neoplastic polyps

BACKGROUND Lipid metabolism reprogramming is suspected to exist in pre-cancerous lesions,including colorectal adenoma.Screening colonoscopy frequently reveals chicken skin mucosa(CSM;white or yellow-white speckled mucosa)surrounding colo-rectal polyps,caused by macrophages engulfing and accumulating the lipids decomposed by colon cells or adjacent tumors.CSM-positive colorectal polyps are associated with various diseases;however,their prognosis varies greatly.Cold snare polypectomy is commonly used to resect lesions up to 10 to 15 mm in diameter without signs of submucosal invasion but is controversial for CSM-positive colorectal polyps.Improved imaging is required to diagnose and treat CSM-positive colorectal polyps.METHODS This retrospective cohort study included 177 patients with CSM-positive colorectal polyps diagnosed using endoscopy.All patient-related information was extracted from the Goldisc soft-clinic DICOM system or electronic medical record system.Based on the pathological results,patients were classified as non-neoplastic polyps(five juvenile polyps),neoplastic polyps,non-invasive high-grade neoplasia(NHGN),or submucosal invasive carcinoma(SM stage cancer).We analyzed and compared the clinical features,suspected risk factors for malignant transformation of neoplastic polyps,and early infiltration of sub-mucosal carcinoma.RESULTS The diameters of NHGN and SM polyps were much smaller than those of neoplastic polyps.Most NHGN polyps had a deeper red mucosal color.On logistic regression analyses,diameter and deeper red mucosal color were independent risk factors for malignant transformation of neoplastic polyps.Type 1 CSM was more common in high-grade intraepithelial neoplasia and SM;type 2 CSM was more common in neoplastic polyps.Logistic regression analyses revealed no significant differences in the malignant transformation of neoplastic polyps or early submucosal invasion of CSM-positive colorectal cancer.Changes in the CSM mucosa surrounding neoplastic polyps and submucosal invasion of colorectal cancer disappeared within 12 months.No tumor recurrence was found during either partial or complete endoscopic resection of the CSM.CONCLUSION CSM-positive colorectal polyps>1 cm in diameter or with deeper red mucosa may be related to NHGN.Resection of CSM surrounding colorectal adenomas did not affect tumor recurrence.

Lymph node metastasis from non-melanoma skin cancer

The management of non-melanoma skin cancers metastatic to the neck is challenging due to variability in biological behavior and patterns of regional lymphatic spread.Metastatic non-melanoma skin cancers to the parotid and neck often behave aggressively,with a high incidence of local recurrence after treatment and reduced five-year survival outcomes.Patterns of lymphatic spread are different from those seen in mucosal squamous cell carcinoma,with higher prevalence of disease in the parotid and superficial lymphatics.These factors require that treatment is individualized to achieve optimal outcomes.Traditionally,the management of non-melanoma skin cancers metastatic to lymph nodes has involved surgical excision followed by adjuvant radiation therapy.However,novel systemic therapies are showing promising results and their role in the management of these cancers is evolving.

Clinical Effect of Photodynamic Therapy Combined Cryotherapy on Nonmelanoma Skin Cancer

The purpose of this study was to investigate the clinical efficacy of photodynamic combined freezing in patients with non-melanoma skin cancer(NMSC).First,according to the treatment regimen,96 patients with NMSC were divided into study group(n=50)and control group(n=46).The control group was treated with 5-amino-ketovalic acid photodynamic therapy(ALAPDT),while the study group was treated with ala-PDT combined with cryotherapy.Visual analogue scale(VAS)scores,visual satisfaction,clinical efficacy,adverse reactions,and progression-free survival were compared between the two groups.The results showed that VAS score in the study group was slightly higher than that in the control group,but the difference was not statistically significant(P>0.05).The appearance satisfaction and total effective rate of patients in the study group were higher than those in the control group,and the difference was statistically significant(P<0.05).The total incidence of adverse reactions in the study group was slightly higher than that in the control group,but the difference was not statistically significant(P>0.05).3 years progressionfree survival time and 3 years progression-free survival rate were compared between the two groups,and the difference was not statistically significant(P>0.05).Therefore,the combination of PDT and cryotherapy for non-melanoma skin cancer has a good clinical effect,which is conducive to the recovery of skin lesions,high patient satisfaction,fewer adverse reactions,and longer progression-free survival.In addition,the combined therapy can provide a new treatment idea for non-melanoma skin cancer patients who are not suitable for surgical treatment.

Treatment of Skin Reaction Induced by Nivolumab Combined with Radiotherapy in Non-small Cell Lung Cancer:A Case Report

Skin reaction or dermatological toxicities induced by immunotherapy is common.It usually manifests skin rash or erythema and can be cured by skin lotion or steroid.Nivolumab,a human IgG4 programmed cell death protein 1(PD-1)inhibitor,blocks T cells activation preventing signal and allows the immune system to clear cancer cells.Nivolumab was approved in the second-line therapy in squamous cell lung cancer by FDA,with less than 10%unusual skin reaction,like sensory neuropathy,peeling skin,erythema multiforme,vitiligo,and psoriasis.Radiotherapy could aggravate this skin reaction through inflammatory response and promotion of immunity.The combined treatment of anti-PD-1 and radiotherapy represented a new promising therapeutic approach in many studies,but the risk of side effects may be high.We reported a patient with advanced squamous cell lung cancer who suffered from serious skin immune-related adverse events when he was treated with nivolumab and radiotherapy.The immune overreaction of the treatment of anti-PD-1 treatment and radiotherapy might cause these serious skin adverse events.Our report warranted careful workup to reduce the risk of side effects by combinative therapy with anti-PD-1 and radiotherapy.

Treatment of Non Melanoma Skin Cancers: An Intra-Comparison Study of CuradermBEC5 and Various Established Modalities

Dermatologists, surgeons, oncologists and radiotherapists usually jointly manage skin cancers. The strengths and limitations of the established procedures are known. A new naturally derived topical cream, CuradermBEC5, for the treatment of non melanoma skin cancers has previously been described. In this communication, intra-comparison treatments of skin cancer between CuradermBEC5 therapy and the established treatments, surgery, radiation therapy, laser therapy, photodynamic therapy, imiquimod cream and cryosurgery are presented. Non melanoma skin cancer cases that had previously been treated unsuccessfully with the established procedures were subsequently treated successfully with CuradermBEC5. These observations are interesting because the identical lesions were treated by various modalities. In addition to the superior efficacious outcome of CuradermBEC5 therapy versus the established treatments, the cosmetic end results with CuradermBEC5 treatment are remarkable.

The Research of Nanocrystallized Realgar for the Treatment of Skin Cancer

Objective: To observe the effects and mechanisms of nanocrystallized realgar for the treatment of skin cancer. Methods: The clinical part was observing the therapeutic effect for the skin ulceration by externally using the nanocrystallized realgar. The experimental part was culturing the human squamous cell carcinoma A431 cells (A431) in vitro environment, estimating the effects of proliferation and apoptosis of A431 by MTT method and flow cytometry, and observing the effects on the expression of Survivin, Caspase-3 by RT-PCR method. Results: External treatment with nanocrystallized realgar had a therapeutic effect for the skin ulceration;it can promote the ulcers of skin cancer and skin metastasis healing. The experiments confirmed that nanocrystallized realgar can inhibit the A431 proliferation, induce the cells apoptosis, promote the expression of Caspase-3 and reduce the expression of Survivin. And the experiments also found that the effects were in a concentration-dependent manner, and they have a synergistic effect with cis-Dichlorodiamineplatinum (DDP). Conclusions: External treatment with nanocrystallized realgar for the patients of skin cancer or skin metastasis achieved satisfactory therapeutic effects by inhibiting A431 proliferation and inducing these cells apoptosis. The mechanism might be associated with promoting the expression of Caspase-3 and reducing the expression of Survivin.

Biomarkers of skin toxicity induced by anti-epidermal growthfactor receptor antibody treatment in colorectal cancer

Skin toxicity is a common symptom of anti-epidermal rowth factor receptor(EGFR) antibody treatment and is also a predictive marker of its efficacy in colorectal cancer patients. However, severe skin disorders induced by such antibodies negatively impact on the quality of life of patients and decreases drug compliance during treatment. If we can predict the high-risk group susceptible to severe skin toxicity before treatment, we can undertake the early management of any arising skin disorders and formulate a more accurate prognosis for anti-EGFR antibody treatment. Previous studies have identified molecular markers of skin toxicity induced by anti-EGFR antibody, such as EGFR polymorphisms, the expression of inflammatory chemokines and serum levels of EGFR ligands. A clinical trial was undertaken involving the escalation of cetuximab doses, guided by the grade of skin toxicity observed, such as no or low-grade, in metastatic colorectal cancer(the EVEREST study). The dose escalation of cetuximab was confirmed by a safety profile and had the tendency to achieve a higher response rate in KRAS wild-type patients. A large, prospective randomized trial is now ongoing(EVEREST 2) and the results of this trial may contribute to personalized medicine in KRAS wild-type colorectal cancer patients.

Computer Decision Support System for Skin Cancer Localization and Classification

In this work,we propose a new,fully automated system for multiclass skin lesion localization and classification using deep learning.The main challenge is to address the problem of imbalanced data classes,found in HAM10000,ISBI2018,and ISBI2019 datasets.Initially,we consider a pretrained deep neural network model,DarkeNet19,and fine-tune the parameters of third convolutional layer to generate the image gradients.All the visualized images are fused using a High-Frequency approach along with Multilayered Feed-Forward Neural Network(HFaFFNN).The resultant image is further enhanced by employing a log-opening based activation function to generate a localized binary image.Later,two pre-trained deep models,Darknet-53 and NasNet-mobile,are employed and fine-tuned according to the selected datasets.The concept of transfer learning is later explored to train both models,where the input feed is the generated localized lesion images.In the subsequent step,the extracted features are fused using parallel max entropy correlation(PMEC)technique.To avoid the problem of overfitting and to select the most discriminant feature information,we implement a hybrid optimization algorithm called entropy-kurtosis controlled whale optimization(EKWO)algorithm.The selected features are finally passed to the softmax classifier for the final classification.Three datasets are used for the experimental process,such as HAM10000,ISBI2018,and ISBI2019 to achieve an accuracy of 95.8%,97.1%,and 85.35%,respectively.

Skin Sparing Mastectomy in Locally Advanced Breast Cancer: A Possibility?

Breast cancer is the second most common cause of cancer death in women in India in spite of advances in the adjuvant treatment of breast cancer. Locally advanced breast cancer (LABC) still represents the major presenting picture in many urban and rural institutions in our country. Skin Sparing Mastectomy (SSM) and primary reconstruction is a popular option for patients with breast cancer. There are similar local and distant recurrences in SSM compared to the traditional non-skin sparing mastectomy. A 57-year-old lady presented with a locally advanced left breast cancer. After undergoing neoadjuvant chemotherapy and a PET-CT to accurately detect residual disease in breast and axilla, she underwent skin sparing mastectomy with nipple-areola complex preservation and primary reconstruction with silicon prosthesis implant over a latissimus dorsi myocutaneous flap for primary reconstruction. SSM in LABC has not been reported in the literature so far. This patient is disease free for the past 24 months.